Exploring the future of programmatic marketing

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A recent analyst report made an astute observation that all marketers should consider: It’s not about “digital marketing” anymore – it’s about marketing in a digital world. The nuance there is subtle, but the underlying truth is huge. The world has changed for marketers, and it’s more complicated than ever.

Most consumers spend more time on web-connected devices than television, creating a fragmented media landscape where attention is divided by multiple devices and thousands of addressable media outlets. For marketers, the old “AIDA” (attention, interest, desire and action) funnel persists, but fails in the face of the connected consumer.

When television, print and radio dominated, moving a consumer from product awareness to purchase had a fairly straightforward playbook. Today’s always-on, connected consumer is on a “customer journey,” interacting with a social media, review sites, pricing guides, blogs and chatting with friends to decide everything from small supermarket purchases to big investments like a new house or car.

Marketers want to be in the stream of the connected consumer and at key touch points on the customer journey. But, in order to understand the journey and be part of it, they must be able to map people across their devices. This is starting to be known as cross-device identity management (CDIM), and it is at the core of data-driven marketing.

In short, identity lies at the heart of successful people data activation.

Until very recently, managing online identity was largely about matching a customer’s online cookie with other cookies and CRM data, in order to ensure the desktop computer user was aligned with her digital footprint. Today, the identity landscape is highly varied, necessitating matching ID signals from several different browsers, device IDs from mobile phones and tablets, IDs from streaming devices and video game consoles and mobile app SDKs.

Matching a single user across their various connected devices is a challenge. Matching millions of users across multiple millions of devices is both a big data and data science challenge.

Real one-to-one marketing is only possible when the second party – the customer – is properly identified. This can be done using deterministic data, or information people volunteer about themselves, in a probabilistic manner, where the marketer guesses who the person is based on certain behavioral patterns and signals. Most digital marketing companies that offer identity management solutions take what data they have and use a proprietary algorithm to try and map device signals to users.

The effectiveness of device identity algorithms depends on two factors: the quality of the underlying deterministic data – the “truth set” – and its scale.

Data Quality Matters

There is data, and then there is data. The old software axiom of “garbage in, garbage out” certainly applies to cross-device user identity. Truly valuable deterministic data include things like age, gender and income data. In order to get such data, web publishers must offer their visitors a great deal of value and be trusted to hold such information securely. Therefore, large, trusted publishers – often with subscription paywalls – are able to collect highly valuable first-party user data.

Part of the quality equation also relates to the data’s ability to unlock cross-device signals. Does the site have users that are logged in across desktop, mobile phone and tablet? If so, those signals can be aggregated to determine that Sally Smith is the same person using several different devices. Publishers like The Wall Street Journal and The New York Times meet these criteria.

Scale Is Critical

In order to drive the best probabilistic user matches, algorithms need huge sets of data to learn from. In large data sets, even small statistical variances can yield surprising insights when tested repeatedly. The larger the set of deterministic data –the “truth” of identity – the better the machine is able to establish probability. A platform seeing several million unique users and their behavioral and technographic signatures may find similarities, but seeing billions of users will yield the minuscule differences that unlock the identity puzzle. Scale breeds precision, and precision counts when it comes to user identity.

As digital lives evolve beyond a few devices into more connected “things,” having a connected view of an individual is a top priority for marketers that want to enable the one-to-one relationship with consumers. Reliably mapping identity across devices opens up several possibilities.

Global Frequency Management: Marketers that leverage multiple execution platforms, including search, email, display, video and mobile, have the ability to limit frequency in each platform. That same user, however, looks like five different people without centralized identity management.

Many marketers don’t understand what ideal message frequency looks like at the start of a campaign, and most are serving ads far above the optimal effective frequency, resulting in large scale waste. Data management platforms can control segment membership across many different execution platforms and effectively cap user views at a “global” level, ensuring the user isn’t over-served in one channel and underserved in another.

Sequential Messaging: Another benefit of cross-device identity is that a user can be targeted with different ads based on where they are in the consumer journey. Knowing where a consumer is in an established conversion path or funnel is a critical part of creative decisioning. Optimizing the delivery of cross-channel messages at scale is what separates tactical digital marketers and enterprise-class digital companies that put people data at the heart of everything they do.

Customer Journey Modeling: Without connecting user identity in a centralized platform, understanding how disparate channels drive purchase intent is impossible. Today’s models bear the legacy of desktop performance metrics, such as last click, or have been engineered to favor display tactics, including first view. The true view of performance must involve all addressable channels, and even consider linear media investment that lacks deterministic data. This is challenging but all but impossible without cross-device identity management in place.

The ubiquity of personal technology has transformed today’s consumers into “digital natives” who seamlessly switch between devices, controlling the way they transmit and receive information. Marketers and publishers alike must adapt to a new reality that puts them in control of how editorial and advertising content is accessed. Delivering the right consumer experience is the new battleground for CMOs. Unlocking identity is the first step in winning the war.

Twenty years after the first banner ad, the programmatic media era has firmly taken hold. The Holy Grail for marketers is a map to the “consumer journey,” a circuitous route filled with multiple addressable customer touchpoints. With consumers spending more of their time on mobile devices – and interacting with brands like never before through social channels, review sites, pricing comparison sites and apps – how can marketers influence customers everywhere they encounter a brand?

It’s a tough nut to crack, but starting to become an achievable reality to companies dedicated to collecting, understanding and activating their data. Marketers are starting to turn towards data management platforms (DMP), which help them connect people with their various devices, develop granular audience segments, gain valuable insights and integrate with various platforms where they can activate that data. In addition to technology, marketers also have to configure their entire enterprises to align with the new data-driven realities on the ground.

The question is: Where do marketers turn for help with this challenging, enterprise-level transition?

Many argue that agencies cannot support the type of deep domain expertise needed for the complicated integrations, data science and modeling that has become an everyday issue in modern marketing. But should data management software selection and integration be the sole province of the Accentures and IBMs of the world, or is there room for agencies to play?

For lots of software companies, having an agency in between an advertiser and their marketing platform sounds like a problem to overcome, rather than a solution. Many ad tech sellers out there have lamented the process of the dreaded agency “lunch and learn” to develop a software capability “point of view” for a big client.

Yet, there are highly compelling ways agencies add value to the software selection process. The best agencies insert themselves into the data conversation and use their media and creative expertise to influence what DMPs marketers choose, as well as their role within the managed stack.

From Digital To Enterprise

It makes perfect sense that agencies are involved with data management. The first intersection of data and media added the “targeting” column to the digital RFP. Agencies have started to evolve beyond the Excel-based media planning process to start their plans with an audience persona that is developed in conjunction with their clients. Today, plans begin with audience data applied to as many channels as are reachable. Audience data has moved beyond digital to become universal.

Agencies have also been at the tip of the spear, both from an audience research standpoint (understanding where the most relevant audiences can be found across channels) and an activation standpoint (applying huge media budgets to supply partners). Since they are on the front lines of where media dollars are expressed, they often get the first practical look at where data impacts consumer engagement. During and after campaigns conclude, the agency also owns the analytics piece. How did this channel, partner and creative perform? Why?

Having formerly limited agencies to doing campaign development and execution, marketers are now turning to the collected expertise of their agency media and analytics teams and asking them to embed the culture of audience data into their larger organization. When it’s time to select the DMP—the internal machine that will drive the people-based marketing enterprise—the agency is naturally called upon.

Data Management Is About Ownership

Although a small portion of innovative marketers have begun leveraging DMP technology and taken media execution “in-house,” the vast majority stills relies on agencies and ad tech platform partners to operate their stacks through a managed services approach. Whether a marketer should own the capability to manage its own ad technology stack is a matter of choice, but data ownership shouldn’t be. Brands may not want to own the process of applying audience data to cross-channel media, but they absolutely must own their data.

Where Agencies Play in Data Management

The Initial Approach: Most agencies have experience leveraging marketers’ first-party data through retargeting on display advertising. In an initial DMP engagement, marketers will rely on their agencies to build effective audience personas, map those to available attributes that exist within the marketer’s taxonomy and apply the segments to existing addressable channels. Marketers can and should rely on past campaign insights, attribution reports and other data insights from their agencies when test-driving DMPs.

Connect the Dots: For most marketers, agencies have been the de-facto connector of their diverse systems. Media teams operate display, video and mobile DSPs, ad serving platforms, and attribution tools. Helping a marketer and their DMP partner tie these execution platforms together, understand audience data, and the performance data generated from campaigns is a critical part of a successful DMP implementation.

Operator: Last, but not least, is the agency as operator of the DMP. Marketers want their data safely protected in their own DMP, with strong governance rules around how first-party data is shared. They also need a hub for utilizing third-party data and integrating it with various execution and analytics platforms. Marketers may not want to operate the DMP themselves, though. Agencies can win by helping marketers wring the most value from their platforms.

Marketers have strong expertise in their products, markets and customer base – and should focus on their core strengths to grow. Agencies are great at finding audiences, building compelling creative and applying marketing investment dollars across channels, but are not necessarily the right stewards of others’ data.

Future success for agencies will come from helping marketers implement their data management strategy, align their data with their existing technology stack and return insights that drive ongoing results.

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With companies like Kraft and Kellogg’s starting to leverage the programmatic pipes for equity advertising, we are starting to hear a lot of buzz about the potential for “programmatic branding,” or the use of ad tech pipes to drive upper-funnel consumer engagement.

It makes sense. Combine 20 years in online infrastructure investment with rapidly shifting consumer attention from linear to digital channels, and you have the perfect environment to test whether or not digital advertising can create “awareness” and “interest,” the first two pieces of the age old “AIDA” funnel.

The answer, put simply, is yes.

Online reach is considerably less expensive than linear reach, and we are starting to have the ability to reliably measure how that brand engagement is generated. Marketers don’t just want an “always-on” stream of brand advertising that comes with measurement – they also need it. With attention rapidly shifting from traditional channels, investments in linear television are starting to return fewer sales.

But most marketers are just starting to gain the digital competency to make programmatic branding a reality. That competency is called data management – the ability to segment, activate and analyze consumer audiences in a reliable way at scale.

The most fundamental problem with digital branding is that it is truly a one-to-one marketing exercise. If we dream of the “right message, right person, right time,” then matching a user with her devices is table stakes for programmatic branding. How do I know that Sally Smith on desktop is the same as Sally Smith on tablet?

Cross-device identity management is the key. Device IDs must be mapped to cookies, other mobile identifiers and Safari browser signals to get a sense of who’s who. Once you unlock user identity, many amazing things become possible.

Global Frequency Capping

One of the reasons programmatic branding has yet to gain serious ground with marketers is because of waste. This is both real, including all those wasted impressions due to invisible ads or robotic traffic, and perceived, such as impressions that are ineffective due to frequency issues.

Smart technology and market pricing solves the first problem, while data management solves the second. Assuming the marketer understands the ideal effective frequency of impressions per channel, or on a global basis, a DMP can manage how many impressions an individual sees by controlling segment membership in various platforms. Let’s say, for example, the ideal frequency for cereal advertising aimed at moms is 30 per day across channels. The advertiser knows showing fewer than 30 impressions reduces effectiveness, while more than 30 impressions has a negligible impact. Advertisers using multiple channels, such as direct-to-publisher, plus mobile, video and display DSPs, are likely overserving impressions in each channel and possibly underserving in key channels like video. Connecting user identity helps control global frequency and can save literally millions of dollars, while optimizing the effectiveness of cross-channel advertising.

Sequential Messaging

If “right person” technology is enabled as above, the next logical step is to try and get to “right place and right time.” Data management can enable this holy grail of branding, helping marketers create relevance for consumers as they embark on the customer journey. What brand marketers have dreamed of is now possible and starting to happen.

Dad, in the auto-intender bucket, is exposed to a 15-second pre-roll ad before logging into his newspaper subscription on his tablet in the morning. The message is reinforced by more equity display ads he sees in the afternoon at work. And while checking messages on his mobile phone on the way home, he receives an offer for $500 off with a qualified test drive. After Dad hits the dealership and checks in through the CRM system, he receives an email thanking him for his visit and reminding him of the $500 coupon he earned.

These tactics are not possible without tying user identity and systems together. Doing so not only enables sequential messaging, but also the ability to test and measure different approaches through A/B testing.

Cross-Channel Attribution

How about attribution? It’s impossible to perform cross-channel attribution without knowing who saw what ad. At the end of the day, it’s really about the insights.

Procter & Gamble is famous for spending millions of dollars every year to understand the “moment of truth,” or why people choose Tide over another detergent. Although they know consumer segmentation and behavior better than anyone, even the biggest brand marketers struggle to gain quality insights from digital channels.

Data management is starting to make a more reliable view possible. Brand advertising is just another form of investment. Money is the input. The output is sales and, just as important, the data on what drove those sales. In the past, brand marketers relied on panel-based measurement to judge campaign effectiveness. Now, data management helps brands understand which channels drove results and how each contributed.

It is early days for truly reliable cross-channel attribution modeling, but we are finally starting to see the death of the “last-click” model. Smart marketers use data to author their own flexible attribution models, making sure all channels involved receive variable credit for driving the final action. In the near future, machine learning will help drive dynamic models, which flex over time as new signals are acquired. We will then start to see just how effective – or not – tactics like standard display advertising are for driving upper-funnel engagement.

Is 2015 the year for programmatic branding? For marketers that are leveraging data management to enable the best practices outlined above, the answer is yes. The more accurately marketers can map online user identity and understand results, the more investment will flow from linear to addressable channels.

In this increasingly cross-device world, marketers have been steadily losing the ability to connect with consumers in meaningful ways. Being a marketer has gone from three-martini lunches where you commit to a year’s worth of advertising in November to a constant hunt for new and existing customers along a multifaceted “customer journey” where the message is no longer controlled.

Consumers’ attention migrates from device to device, where they spread their limited attention among multiple applications. It’s become a technology game to try and track them down, and starting to become a big data game to serve them the “right message, at the right place, at the right time.”

Modern ad tech is supposed to be the marketer’s savior, helping him sort out how to migrate budgets from traditional media, such as TV, radio and print, to the addressable channels where people now spend all of their time. Marketers and their agencies need a technology “stack,” but they end up with a hot mess of different solutions, including various DSPs for multiple channels, content marketing software and ad servers.

Operating and managing all of them is possible, but laborious and difficult to do right. Worse still, these systems are nearly impossible to connect. Am I targeting the same consumer over and over through various channels? How to manage messaging, frequency and sequencing of ads?

Since all of these systems purport to connect marketers to customers on the audience level, the coin of the realm is data. It’s not just “audience data” but actual data on the individuals the marketer wants to target.

Marketing is now a people game.

Yet, in the cross-channel, evolving world of addressable media, connecting people to their various devices is difficult. You need to see a lot of user data, and you have to not only collect web-based event data, but also mobile data where cookies don’t exist. Deterministic data, such as a website’s registration data, can lay the foundation for identity. When blended with probabilistic data and modeled from user behavior and other signals, it becomes possible to find an individual.

Right now, the overlords of the people marketing game are platforms like Google, where people are happy to stay logged in to their email application on desktop, mobile and tablet, or Facebook, which knows everything because we are nice enough to tell them. Regular publishers may be lucky enough to have subscription users that log in to desktop and mobile devices, but most publishers don’t collect such data. Their ability to deliver true one-to-one marketing to their advertisers is limited to their ability to identify users.

This dynamic rapidly makes the big “walled gardens” of the Internet the only place big marketers can go to unlock the customer journey. That might work for Google and Facebook shareholders and employees, but it’s not good for anyone else. In our increasingly data-dependent world, not all marketers are comfortable borrowing the keys to user identity from platforms that sell their customers advertising. Soon, everyone will have to either pay a stiff toll to access such user data, or come up with innovation that enables a different way to unlock people-centric marketing.

What is needed is an independent “truth set” that advertisers can leverage to match their anonymous traffic with rich customer profiles, so they can actually start to unlock the coveted “360-degree view of the user.” Not only does a large truth set of users create better match rates with first-party data to improve targeting, but it also holds the key to making things like lookalike modeling and algorithmic optimization work. Put simply, the more data the machine has to work with, the more patterns it finds and the better it learns. In the case of user identity, the probabilistic models most DMPs deploy today are very similar. Their individual effectiveness depends on the underlying data they can leverage to do their jobs.

In the new cross-device reality: If you can’t leverage a huge data set to target users, it’s time to take your toys and go home. Little Johnny doesn’t use his desktop anymore.

Think about the three principle assets most companies have: their brand, their intellectual property and products and their customer data. Why should a company make a third of their internal value dependent upon a third party, whether or not they pledge “no evil?” Those that offer a “triple play” of mobile, cable television and phone services are also part of the few companies that can match a user across various devices. The problem? They all sell, or facilitate the sale of, lots of advertising. Marketers are not sure they want to depend on them for unlocking the puzzle of user identity.

Some of the greatest providers of audience data are independent publishers who, banded together, can create great scale and assemble a truth set as great as Facebook and Google. Maybe it’s time to create a data alliance that breaks the existing paradigm. The “give to get” proposition would be simple: Publishers contribute anonymized audience identity data to a central platform and get access to identity services as a participant. This syndicate could enable the deployment of a universal ID that helps marketers match consumers to their devices and create an alternative to the large walled gardens.

The real truth is that, without banding together, even great premium publishers will have a hard time unlocking the enigma of cross-device identity for marketers. Why not build a garden with your neighbors, rather than play in somebody else’s?

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Back in 2007, a company called TRAFFIQ started one of the first programmatic futures exchanges. The idea was simple: publishers committed blocks of premium inventory into the exchange at a stated price (say, a block of 500,000 homepage rectangle units in November at $8 CPM), and advertisers could construct packages of premium inventory at discounted prices by making future commitments. Basically, a better, faster way to buy digital guaranteed.

The idea never really took off. Publishers didn’t really understand how to value their inventory in the future, real-time enablement was just starting to take off, and advertisers and their agencies were deeply stuck in manual inventory procurement run by spreadsheets and fax machines. (TRAFFIQ went on to build some highly innovative workflow automation software, and is now a successful technology- enabled digital agency).

Almost eight years later, we are living in a fully programmatic world—but many of the benefits of programmatic futures have yet to come true. Today’s “programmatic” is still very focused on RTB, inventory pools are still murky, and technology’s ability to value publisher inventory still has a long way to go. What’s missing?

The problem with today’s programmatic RTB environment is that the “exchanges” aren’t really true exchanges like we have in the financial markets. Although you can liken online inventory to stocks, the comparison is tough to justify. Lacking agreed measurement, value continues to be in the eye of the beholder. More importantly, the procurement process is still driven more by the buyers than the sellers. Private exchanges are starting to make inroads in terms of creating valid counterparty transactions, but the RTB pipes have not been engineered to handle the key aspects of transactional workflow.

The biggest, fundamental problem with RTB is that it values inventory in a singular way. In the open market, a 30-year old male car intender costs the same whether you find him on Cars.com or Hotmail. Although tweaks in RTB with private transactions can enable premium inventory procurement, it’s not scalable. The right exchange should be able to value audience separately from everything else.

Another issue is the problem of valuing inventory over time. As a publisher with 30 days to go in my quarter, my homepage inventory may be worth $10CPM. But, the day before the quarter closes, that same inventory may be worth only $1CPM if I haven’t sold it yet. Today’s networks and exchanges enable publishers to set a solid floor price, but have trouble managing value dynamically. That’s because future publisher pricing is not being matched with visible demand. Ironically, the real-time nature of today’s exchanges actually limits a publisher’s ability to manage yield, because every impression is always chasing an immediate bid. A real futures exchange would enable a publisher to value inventory dynamically, so it matches the value set not by bids—but by buy orders in the system (real, stated demand for future inventory).

Although the demand side has it pretty good right now, a true programmatic futures exchange could be truly game changing. Yes, today’s exchanges are serious arbitrage machines. Because the buyer has access to the entire market, they have more information available to them to manage their investment. The problem is, in programmatic RTB, they are stuck with a two-tiered system: secure “premium” inventory through private exchanges and/or DealID functionality for branding and demand creation, and drive lower-funnel activity through performance-driven bidded buying in the wilds of the exchange. Ask any trading desk manager—it’s still really hard to get exactly what you want without going to guaranteed buys, cross-channel buying still requires multiple systems, and communicating the value of the “media investments” you are making to clients is near impossible, because everything is bought and measured differently. So, going from “media buying” to true “media investment” necessitates a true programmatic future exchange, akin to NASDAQ or the NYSE.

In such an exchange, publishers would be able to value their inventory by utilizing a combination of their existing rate cards and product catalogs (for selling advance contracts), and data from buy orders in the market itself. Just like in the stock market, prices would fluctuate based on the spread between bid and ask pricing—and the contract date. Publishers could therefore execute any type of guaranteed buy in such a system (direct sales) as well as have the exchange handle direct deals (“programmatic direct” and “private market”). This is because such an exchange would manage matchmaking, not the execution piece. This is critical. Today, we are watching systems built from the ground up to deliver ads try and go in reverse to manage the process of buying them. As we have seen, the rise of “automated guaranteed” platforms suggests that RTB is not quite cut out for the job.

Why would the demand side want a true programmatic futures exchange? First of all, a true futures exchange treats media as a true commodity—and makes it tradable. The beauty of a commodities exchange is that, once you own a future contract for pork bellies, you can sell it. In digital media, once you have bought a bunch of 300x250s in Appnexus, you are stuck with them. Arbitrage is not the same as futures trading in a regulated market. A true programmatic futures exchange for media would actually enable well-heeled buyers to leverage their scale to consolidate positions in media, and resell them in bulk (or in chunks). Think about that. Imagine GroupM buying the entire Q4 consumer electronics inventory in February. What would that be worth to another agency representing Sony as the holidays approached?

The bottom line is that, despite the power of RTB pipes, we are a long way away from seeing the platforms where addressable media will be traded in the future. Eight years ago, my bet was on a programmatic futures exchange, and I am still long.

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Mobile is truly the biggest opportunity in advertising right now. Sorry, but nothing else even comes close.

Not only are mobile devices nearing ubiquity – but research shows they’re owned by more than nine out of 10 earthlings – smartphones are nearing ubiquity in the developed world, too, with 56% penetration. People are on mobile all the time, and more than half of them use the mobile device as the primary way they access the Internet. At 1.8 hours a day, media consumption on mobile devices now surpasses both television (1.5 hours) and desktop (1.6 hours). If marketers would match their investment in mobile advertising, now at just 4% of media budgets, with the amount of time we spend there – 20% of our time – a lot of people would make a lot of money.

Mobile is now “first among equals” when it comes to marketing channels, and every advertiser should think that way when they start putting their plans together for 2015.

Everything Has Already Changed Forever

Proctor and Gamble loves to talk about “the moment of truth,” which is when a consumer stands in front of a store shelf and chooses between two products. Why did they buy Tide detergent instead of Surf? There are a lot of emotional connections between brands and people, whether you are buying soap or making a decision on your next high-ticket item, like a dishwasher. Although brands still need to make an emotional connection, there is an entirely new dynamic driving the many different “moments of truth” we have every day.

Today, we also have what Google calls the “zero moment of truth,” or the fact that every consumer with a smartphone can find out when they are standing in front of that shelf every good and bad thing ever written about a product. So, as a marketer, how do you handle that every one of your customers has the acquired knowledge of the universe in their hands at all times? They can get all the reviews, see all the coupons and deals, and ask their friends before making a decision. That’s going to keep us all busy for years to come in ad tech.

Stop Saying ‘Funnel’

Mobile killed the sales funnel. Somehow, over the last year or so, the AIDA funnel died a quiet death after 116 years. The idea of driving potential customers through a process of “attention, interest, desire and action” has been replaced with something we now call the “customer journey” – a circuitous route, where marketers must be in control, or quickly able to react to, all kinds of touchpoints.

If that sounds confusing, you are not alone. Most marketers struggle with the sheer data expertise needed to create and build sequential messages that follow a consumer from television to tablet to smartphone as they learn more about brands or products. In 2014, the customer journey is mostly handled through retargeting on as many devices as possible, but the lack of a universal ID makes telling a good story across screens pretty tough.

If you want to be able to do that as a marketer, or help marketers do that on your audience as a publisher, then it’s all about the data.

The Tom Cruise Thing

At every mobile conference, someone usually shows a slide with Tom Cruise from “Minority Report.” In the 2002 movie – released more than a decade ago! – we saw future Tom walking by interactive DOOH billboards for Lexus and the Gap, receiving all kinds of personalized offers after being retina scanned. Everything in that movie now exists, including facial identification, in-store beacons, real-time creative delivery, geolocation, RFID and personalization.

We are living in a “Minority Report” world, and sooner or later, we are going to figure out how to put all of the pieces together at scale. Was that a mobile ad that Tom Cruise saw, or will we be calling it something else? Does it matter?

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I recently tried to explain what I do for a living to my 14-year-old son. I found myself telling him about ad tech.

“Basically, we make technology that helps marketers buy different kinds of banner ads,” I told him.

“You mean the kind of annoying pop-up ads that everyone hates?” he asked.

His look of profound disappointment said it all. I explained that the kind of work we do wasn’t just about populating the Internet with the “Lose five pounds with one stupid trick” type of banner. But even though we are getting a lot right, my explanations eventually started sounding pretty weak.

I have been working in this business since 1995. Aside from doing some ad implementation testing, I have probably clicked on about a dozen banner ads in as many years. Today’s robust, real-time ad tech “stack” has been purpose-built to optimize the delivery of the kind of banner ads most people already hate: standardized IAB units, retargeted ads, auto-play video pre-roll units and even the dreaded pop-up and pop-under.

Publishers without robust direct sales options depend on networks and exchanges to monetize the endless streams of traffic they create, and they happily collect their $1.10 eCPM (cost per mille) payments. Advertisers looking for cheap reach and performance plumb the depths of such inventory to find the rare conversion, and hope they are getting what they pay for rather than a shady “last view” attributed banner.

Today, the highest and best use of the standardized banner has enabled marketers to leverage their first-party data to bombard site visitors with retargeted ads – an effective tactic, since they are essentially paying to accelerate a conversion that has a great chance of happening on its own.

As an industry, it seems pretty clear that we will look back on this era in digital ad technology and see how primitive it was. Have we built a trillion-dollar real-time ad serving machine for punch-the-monkey ads, or have we really innovated and created disruption?

RTB Is Dead, Long Live RTB

The recent acquisition of [X+1] by Rocket Fuel is a great sign for our industry. It basically validates the idea that, for programmatic RTB to be effective, real data science must inform targeting. [X+1] is one of the best at cross-channel targeting, and they have already started to figure out the cross-channel attribution puzzle. An everlasting always-on stream of RTB banners for branding and retargeting might prove to be a hugely important part of unlocking a broader multi-channel strategy – if the data can dictate it. If data management platform technology can be leveraged to truly optimize addressable marketing, then RTB will survive and thrive. With consumers always on the move, and every form of media starting to be addressable, real-time programmatic will be something marketers have permanently switched on, and we’ll see the true value of the pipes we have created.

Programmatic Direct

How about inventory that is relatively standard, but a bit nicer than that found within the exchange environment? Transacting on this tier of inventory works quite nicely with all kinds of one-to-one connections within RTB, and buyers and sellers are quickly leveraging the pipes to make private marketplace deals.

If I am a quality financial publisher, why wouldn’t I sell within RTB for $8 CPMs, rather than pay a $200,000 salesperson to sell at $12 CPMs? The math just makes sense. Delivering higher tiers of inventory at scale to private buyers is a great use of RTB, but not a panacea for overall inefficiency in media procurement. But, we have seen those RTB pipes service entire new classes of inventory, and start to appeal to brand marketers.

Workflow Automation

The problem with getting really good inventory has always been the difficulty understanding rates and availability. That’s why the RFP exists today, and isn’t going away anytime soon. Publishers will always want full control over the really good stuff. Because they know their inventory better than any algorithm, there will always be a need for human control and creativity. Big, custom sponsorships and custom-curated native executions will only increase over time, as more television and print budgets shift into addressable digital. You just can’t automate those deals. Marketers and agencies will demand programmatic efficiency to compress an expensive, 42-step process for securing guaranteed inventory. This is one area that programmatic RTB has not been built to handle (these deals are neither “real time” nor “bidded”), but we are seeing real innovation from a number of companies trying to bring programmatic efficiency to guaranteed deals.

It’s hard to explain everything that we are getting right to a 14-year-old who spends more time on mobile apps than in an Internet browser. His assessment, in surfing the desktop Internet, is probably right – it looks like a lot of weight loss ads and sneaker retargeting. But, it’s still early days nearly 20 years after the first banner ad was served.

The New Mobile Display Ecosystem, an Econsultancy report published in association with OpenX, surveyed over 20 leaders in mobile marketing, publishing, and technology to find out the latest trends in mobile advertising, and what the future might hold. Chris O’Hara, the report’s author, answers some of our questions about the research.

So, is 2014 finally the “year of mobile?”

Well, this “year of mobile” has been coming for some time, but our survey panelists are starting to feel that mobile has finally emerged as a player on the overall advertising scene. There are still huge discrepancies between time spent on mobile devices (a lot) and ad spending in the sector (relatively small). According to some research, people spend more than 20% of their time on mobile devices, but ad spending is at 4%. That’s a multiple-billion dollar opportunity.

What is keeping mobile ad spend from growing?

Our research showed that a large issue for advertisers was mobile creative—specifically, the lack thereof. The units are mostly small and prone to “fat thumb” clicks in browsers, and most of the in-app ads were fairly plain “install ads.” Not great for brand building or telling a story. Also, it is still somewhat difficult to get to scale without a “mobile cookie,” or persistent ID. That’s changing now, but without having statistical identification available at scale across many systems, only the large players like Google and Apple can effectively identify users across devices. That’s a challenge.

Who is most impacted by the growth in smartphones in the ad ecosystem?

For me, the retailers and product folks have it the worst. Soon enough, smartphones will reach 50% penetration. That means every other person will have the combined knowledge of the entire world right at their fingertips. What that means for retailers is what Google is starting to call the “Zero Moment of Truth,” an adaptation of an old P&G saying. What it means is that, when a consumer is standing in front of a product with their smartphone, they can find out every single thing—good and bad—about a product that’s ever been written with the click of a button. And, of course, the right price to pay. That’s an incredible dynamic.

What’s the most shocking thing you learned while researching the report?

You asked panelists what “Mobile First” really means. What did they say?

Everyone agreed that both marketers and publishers have to start with mobile, because that is where people are spending their time. You can’t ignore mobile, or just make an HTML5 site and call it a day. If you are building a new website, launching a new product, you must do that with a “mobile first” approach, and try to leverage the unique touchpoints the channel offers to consumers. That’s the obvious part. I was pretty surprised to see how passionate people were about the idea of “mobile first.” Many think mobile is the biggest single opportunity out there for business. Suffice it to say, it is ignored at your peril.

What about the creative problem? How are marketers taking advantage of the unique data and form factors at play in mobile?

Native is certainly a big focus. The IAB has identified about 6 different categories of native advertising, many of which apply to mobile devices. OpenX has recently launched a new mobile exchange for accessing native mobile units programmatically. Native units tend to leverage more of the mobile form factor, which is great. Marketers are still struggling to take advantage of all the great data that can be used (altitude, motion, facial recognition, biological data, activity, etc), but some really cool executions are starting to be deployed. We are essentially ready for our Tom Cruise “Minority Report” moment from 2002, with ads that can follow us around and talk to us personally based on our situation.

What are the biggest threats?

Although everyone I talked to loves their “triple play” deal, and Apple or Android phone, nobody wants telecoms or big technology companies to be the only ones with cross-device targeting capability. All thr panelists were interested in a more diverse ecosystem, more akin to display advertising, where the “cookie” (albeit controversial) has enabled real audience targeting at scale. Marketers need to tell a sequential story, as the consumer moves from device to device. That’s only possible when you can link users to all of their devices, and that’s hard to do now unless you are Verizon.

Any final thoughts?

I think video is the way we are going to see mobile eat into established marketing budgets. The ads play amazingly well on new larger-screen phones and HD tablets. There are great creatives already established (the 10, 55, and 30 second spot ad), and you can actually tell stories with video, which is what marketers want to do. Videos are also the ultimate “native” ad. Video is where the action is right now, but other native formats suited to mobile form factors will follow.

Digital agencies used to get paid for unpacking an incredibly complicated digital landscape for marketers. Faced with all kinds of new marketing opportunities, advertisers turned to savvy digital agencies to figure out where to spend their money, and how much of it to dedicate to display, mobile and social channels.

The dingy little secret was that the agencies didn’t really plan much of anything. The way it worked was that agency planners would make an Excel template, create an RFP document, instruct the media owners to send back all kinds of creative ideas and fill out the media plan template. RFPs sent publisher teams spinning into action, churning out exciting-looking PowerPoints with screenshots and suggested spending levels.

Not much of this was scientific. Publishers often promised more inventory than could be delivered, knowing they would never get the full budget allocation. Agencies asked for various “budget levels,” knowing they would allocate only $50,000 per publisher – but asking to see $200,000 plans to get a better sense of where CPMs might be negotiated. At the end of the day, the agencies would pick the winners and losers, usually the five publishers on the last plan, plus a few “challengers” or new ideas to impress the client with “innovation.” Once the plan went live, publishers could count on a quick cancellation or massive change to the contracted plan. Nothing ever seemed written in stone once the first impression was served.

Sounds pretty lame, right? Sadly, a lot of media is still planned this way. But, thanks to all kinds of programmatic innovation, times are rapidly changing and digital agencies are going to have to find out how to change with it.
In the old paradigm, agencies largely provided value by dealing with the intricacies of negotiating with vendors, moving data from plans to ad servers and billing systems and keeping clients in the loop on how their digital media “investments” were performing. Optimization was largely defined as cancelling a bad deal and re-allocating budget into a better one.
Today’s ad technology has given marketers and their agencies a lot more knobs and buttons to push. We are rapidly seeing a shift away from manual, Excel-based processes to nimble, web-based planning technology, driven by centralized data.
There are no spreadsheets inside of MediaMath or AppNexus. Publishers don’t offer PowerPoints in iSocket or AdSlot. And agencies are pushing legacy media-buying systems like MediaOcean and Strata to adapt to a digital world without spreadsheets and fax machines. A host of new, web-based planning and buying systems (like Bionic!) are also starting to disrupt the status quo, as agencies try and reconcile the old ways of buying media with a world in which billions of ad impressions are available through interfaces and big clients like P&G say they are going to buy up to 70% of ads programmatically.

Recently, a big European group of publishers introduced an RFP to have their entire digital inventory catalogued and made available through “programmatic direct” technology. Publishers want to give advertisers the efficiency and access they crave but have complete control over pricing and availability. That’s where the world is heading.
So what happens to an agency whose sole digital expertise consists of sending out Excel templates for publishers to fill out with pricing and avails? Sounds like the value they have been providing – lots of manual horsepower to help with complicated workflow – is going to become completely irrelevant. You can buy all the social media you want through easy-to-use interfaces.

It’s easy to hire a few smart “traders” and give them access to a DSP and gain access to the universe of inventory available in programmatic RTB. And now it’s increasingly easy to negotiate premium inventory deals inside programmatic platforms and secure those guaranteed impressions. A number of big marketers have decided it’s so easy that they are starting to do it themselves by bringing digital marketing in-house.
Digital media agencies’ legacy business models are expiring faster than a Madison Avenue parking meter. What should innovative agencies be doing to change and continue to provide real value to their clients?

Planning: “Planning” is not planning anymore. It’s investment management. Even though there are new ways to procure the media, your clients still need to know how it’s performing and moving the needle for their business. Figure out how to measure beyond clicks and common CPA metrics and try to get inside your clients’ real budget numbers. Are you gaining access to the client’s P&L and first-party data so you can help them measure by more important metrics, such as net new customers?

Teaching: Just because desktop display and social ads are commoditized doesn’t mean clients don’t need to understand the latest ways to rise above the noise. Are you schooling your clients on nascent native mobile opportunities or the latest ways to leverage RTB video to enable branding at scale? These are ideas that come with the help of vendors and publishers, but agencies need to stop collating others’ ideas and start helping vendors translate their opportunities into the framework of the client’s business. That is where the right digital agency can provide value.

Doing: The manual, spreadsheet-driven world of “22-year-old media planners” where labor, rather than strategy, was at a premium are over. But, in a programmatic world, execution – the “doing” – is more important than ever. Reallocating budgets to match performance cannot be totally algorithm-driven when spending is across multiple channels in systems that do not speak to each other. Agencies are perfectly positioned to be in the middle of dozens of systems, reconciling spending and performance against both long- and short-term client goals. That’s a job that can only be done by people.

The irony of today is that lot of systems are starting to make digital media planning less complicated from a transactional and workflow standpoint but the overall digital landscape is more complicated to navigate than ever. The digital media agencies that survive must change the way they plan, teach their clients and execute in order to survive and thrive.

Savvy marketers use data mining, data visualization, text analytics, and forecasting to make more effective decisions and reach customers. But the savviest among them are innovating with fresh types of data—and attracting new business as a result.

Sensing Opportunity for an Upsell
“The data that devices collect are going to add all kinds of context to advertising,” says Chris O’Hara, cofounder of Bionic Advertising Systems, a digital advertising service. Marketers can know exactly where potential consumers are, the current time and temperature, and which of the consumer’s friends are nearby.

When might such factors come into play? O’Hara gives the example of sensors in grocery stores that can detect the items shoppers take off the shelves. That data, run through huge databases, enable marketers to instantly suggest—via tech such as smartphones or electronic shelf displays—other products for shoppers to add to their carts.

Adding Location
More and more, geography will help marketers zero in on demographics, says Kevin Lee, CEO of online advertising and marketing firm Didit. “Geotargeting is a great way to market not only at the hyper-local business level but also for national marketers looking to target specific demographic and psychographic groups,” he says.

Marketers have experimented for years with mobile geolocation-centered campaigns, primarily using couponing. However, since research shows that a whopping 72% of consumers say they’ll respond to sales calls-to-action within sight of the retailer, there are plenty more location-based opportunities that encourage customer loyalty, such as special gifts, alerts to flash sales and early access.

Cooking a Data Stew
With the evolution in data analytics, marketers can now mix different types of data to glean new insights. David L. Smith, CEO of media agency Mediasmith, sees this as the coming of age of the data management platform: tools that integrate data from several sources, including customer information, website data and digital advertising input. All of it serves to improve messaging.

“Messages that come from ad campaigns, direct mail and other communications to the consumer can be coordinated,” Smith says, “so that the consumer is always getting relevant information—not just standard communications.”

Collecting Data—While Respecting Customer Privacy and Security
All these data-driven trends can bring benefits to the consumer and improve marketing efficiency. But they also raise privacy and security issues—to which marketers are giving serious attention. “Privacy is going to remain a constant fear in the consumer’s heart,” says Michael Hardin, dean at the University of Alabama’s Culverhouse College of Commerce. “A lot of companies are going to be struggling mightily to deal with that.”

Smart marketers will learn how to walk this fine line and mine significant value from relatively little personal information, says O’Hara. One company strikes this balance with one of its products, an activity-tracker wristband: With just a little personal data input from its user, the wristband gives them athletic performance feedback.

These new technologies are changing the world of marketing—especially given the speed at which data are arriving, says Hardin. Shrewd marketers are contemplating how best to react in a way that benefits their companies.

There has been a lot of talk about the pervasive amount of click fraud and bot traffic happening in digital. Marketers are reportedly spending anywhere from 30% to 70% of their digital budgets on fake impressions and clicks, and an entire cottage industry is cropping up to help marketers combat fraud and try and protect their digital marketing investments.

Some people claim that price of fraud is already built into the programmatic RTB ecosystem. Marketers are using programmatic RTB for direct marketing, and they are measuring sales using CPA metrics. If they are paying $100 per verified acquisition, should they care whether it takes 10 million or 20 million impressions to produce a conversion? Some say that they don’t, and take the view that they only pay for results, justified by their backend conversion metrics which take media cost into consideration.

I hope this is not the case. Ignoring fraud with these justifications is what ultimately may kill the digital advertising business before we ever get to scale.

Another big problem is faulty, fraud-like attribution. Let’s take the case of the big programmatic marketing platform that has been getting great conversions for their customers. Marketers look at the results of such platforms and think that the technology has managed to effectively separate the wheat from the chaff in popular ad exchanges and find the “sweet spot” of cookie targeting that converts. But, dig a little deeper and you notice that many of the conversions are happening on webmail subdomains (mail.yahoo.com). In other words, the platform is getting last-view attribution from successful e-mail marketing. This is a more subtle case of fraud…but really more of a tax on digital ignorance for marketers. But again, the marketer sees this channel producing results that align with his CPA goals. Did the conversions get attributed correctly? Maybe not, but those questions get overlooked when the blended CPA is on target.

Cookie bombing and other types of fraud are just as likely to limit digital advertising to performance budgets, and keep real growth at bay.

If we are being honest with ourselves, we must admit that there doesn’t seem to be a ton of desire to solve these inherent problems in programmatic RTB. There are too many people making too much money to want to fix it. And it’s going to destroy programmatic RTB as we know it. Who benefits from the current scenario?

Publishers: Most publishers benefit greatly from the programmatic RTB revenue stream. Big publishers “fill” their long tail inventory with ads. Mid-sized publishers without large direct sales teams depend greatly on network and programmatic fill for their revenue. Long tail pubs are fully committed to their AdSense checks for survival. A lot of publishers’ Comscore numbers are a lot bigger than they should be, thanks to cheap inventory of unknown provenance.

AdTech: Every vendor in programmatic RTB benefits from inventory flowing through their pipes. Most charge on a percentage-of-spend, which means they might sacrifice 50% of their revenue if they had to stop charging for fraudulent impressions. New fraud detection and measurement firms are also profiting (albeit in a virtuous way).

Agencies: What would today’s big agencies do without the ability to leverage programmatic RTB to arbitrage inventory, or charge a premium for “unpacking the ad tech space” for their clients? The new programmatic landscape has been a boon to smart, nimble agencies that have built, bought, or leveraged ad technology to pivot their dying media businesses. How eager are agencies to expose the fundamental flaws within the programmatic RTB ecosystem?

The biggest loser in the entire room is the poor marketer, who ultimately pays the bills. But it’s easy to turn a blind eye, because the numbers look good. But how long will big marketers confuse true marketing success with today’s flawed digital attribution metrics? Marketers are starting to think about real measurement frameworks (net new customers), rather than CPA metrics. They are also keenly interested using brand messages to interact with their customers across screens. And they won’t be using CPA to measure brand growth.

So why do marketers continue to leverage programmatic RTB despite the inherent risk of fraud and current limitations for brand advertising? To paraphrase Clear Channel’s Bob Pittman at the recent IAB annual meeting, “Given a choice between quality and convenience, convenience always wins.”

The biggest question lately is whether or not we can make it as convenient (and cheap) to buy guaranteed media at scale. Seeing this opportunity, a lot of players in programmatic RTB are looking hard at the money being spent on guaranteed media (the “transactional RFP” channel), and trying to add new “programmatic direct” tools to their arsenals. RTB players know that brands are still uncomfortable executing brand campaigns in the wilds of the open exchange, and they know truly premium inventory won’t be available unless publishers have more granular control over pricing, availability, and partner selection. Put more simply, the lion’s share of digital money still gets transacted manually, with paper insertion orders, and successful automation means a big piece of the action.

Providing a layer of automation for direct deals helps with fraud (guaranteed deals, by their nature, offer inventory transparency), and adds the ability to scale within higher classes of inventory.

Marketers are actually looking forward to having their agencies leverage new technology to secure quality digital placements. Whether these innovations come from tweaking existing programmatic RTB technology (private exchanges) or from new, API-driven “programmatic direct” providers doesn’t matter to them. They need to execute cross-channel digital campaigns at scale, and those campaigns (if they are for brand purposes) cannot contain fraud.

Does this spell the end of programmatic RTB? Nope. I think there will always be exchanges and technologies that let direct marketers plumb the depths of the Web to drive online sales. Ten years ago, folks were writing about the death of shady affiliate, click, and CPA networks—but they are still around. But, will today’s programmatic RTB business have to fundamental transform to win brand dollars? Yes, and the path to success is what we have been calling programmatic direct. It will be interesting to see the various technology executions of programmatic direct, as they form the gateway for branding to flourish online.

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I was recently at a Digital Marketing Association awards dinner where data legend Charles Stryker was being honored. After accepting his award, he told a famous story about data that every digital marketer should know.

A long time ago, the US Postal Service discovered they were paying a ton of money to deliver mail to deceased people. Charles was hired to help them get a handle on their records and create a sort of “Do Not Mail” list. Part of doing the work involved considerable A/B testing to ensure he was making the correct assumptions about the data. Direct response mailers were being sent to groups of dead people and similar groups of folks who were still alive. Something astonishing happened when the results came in.

The dead people responded at nearly twice the rate of the living.

Of course everyone at the dinner (about a hundred senior direct marketing executives) laughed uproariously. They have seen all kinds of unpredictable results with direct marketing. In today’s digital age, marketing is moving faster than ever. The velocity of data is increasing in orders of magnitude, and attribution is going to get even trickier.

What happened with the “dead” people was pretty interesting. It turns out that the successful mailers went to households where the husband of the family died, and the elderly spouses were taking great care to go through and read the mail of their deceased partners. The wives wanted to make sure there was nothing important in those letters—and probably were connecting with their husbands through that simple, daily task. Those widows made a great mailing list “select” since they actually opened and read the mail!

In today’s digital marketing, where we seem increasingly dependent on algorithms and attribution models for targeting and measurement, I wonder if we are too deep in the weeds. Are we forgetting the real, human element of marketing? Do we really understand how success and failure happen with our campaigns? At a recent iMedia agency conference, a lot of the talk was about trying not to forget that advertising is first and foremost about storytelling. Leading with emotion is so important. The marketer has to make an emotional connection with his audience and get them to care.

That struck me when watching a joint town hall workshop with Google and Kellogg’s about dynamic creative. Yes, changing the background color or “call to action” on a 300×250 ad in real time can bump the lift of a campaign incrementally—but are we tweaking a broken process?

Can we really tell great stories on standardized banner ads?

With the rapid rise of programmatic, a lot of platforms and data companies are fully committed to a standardized industry where scale is king. Display, video, and mobile—biddable and accessible at full scale—is the mandate. Kellogg’s wants inexpensive access to a large electronic palette where Frosted Flakes ads can be constantly tweaked to get optimal performance. Nothing wrong with that. American Express recently announced an “100%“programmatic” initiative for digital marketing. Why not? Both companies spend tons of money on TV, and optimizing the bottom of the funnel makes complete and utter sense.

But that’s all we are talking about: Optimizing the bottom of the funnel with standardized ads. Sorry, but we are not creating new customers with dynamic 300×250 ads that get a .05% click-through rate. If you are in this business, working for a venture backed startup or newly public adtech company whose value proposition is around driving audience targeting at scale, then you are not “creating stories” online.

As an industry, we need to create digital campaigns that get people to “open the mail.” This is incredibly hard to do with standard display banners, today’s woeful “native” executions, and interruptive social ads. Video has promise, but scale still eludes marketers, and low video completion rates erode available reach considerably.

So, how do you leverage programmatic technology to get great creative out at scale? The only real answer is to automate the workflow behind securing premium inventory and custom programs. That’s where the promise of programmatic direct comes in. Marketers want great ideas from publishers, access to the best inventory they have, and non-standardized units. They just don’t want to pay 10% of their media budgets for planners to cut and paste data into spreadsheets.

Innovation in the space is not just limited to programmatic direct companies with API connections into the publisher side (iSocket, ShinyAds, AdSlot) and workflow automation players (Centro, MediaOcean, and Bionic Advertising)—but also includes RTB players like Rubicon and MediaMath who are building new automation capabilities to augment their RTB stacks. In other words, it’s all about automating the deal right now.

Do they want access to evergreen programmatic campaigns that drive their most likely customers through the bottom of the sales funnel? Of course, and that’s a great job for programmatic RTB. But it does not, cannot, and will never replace the kind of media you can secure through a guaranteed transaction. Also, speaking of dead people responding better—that kind of sounds familiar. In programmatic RTB, some of the best click-through rates come from the dead—fake visitors created by robots.

That said, I think more and more digital advertising will go programmatic, and that programmatic RTB will command the lion’s share of performance budgets. But, when it comes to building brands, bringing automation to the process of securing quality inventory will win.

Despite years of online targeting, the idea of having a complete, holistic “360 degree view” of the consumer has been somewhat of a unicorn. Today’s new DMP landscape and cross-device identification technologies are starting to come close, but they are missing a key piece of the puzzle: the ability to incorporate key social affinities.

In the nearby chart, you can see that online consumers tell us all about themselves in a number of ways:

Viewing Affinities: Where they go online and what they like to look at provides strong signals of what they are interested in. Nielsen, comScore, Arbitron and others have great viewership/listenership data that is strong on demographics, so we can get a great sense of the type of folks a certain website or show attracts. This is great, but brands still struggle to align demographic qualities perfectly with brand engagement. 34 year old men should like ESPN, but they could easily love Cooking.com more.

Buying Affinities: What about a person’s buying habits? Kantar Retail, OwnerIQ, and Claritas data all tell us in great detail what people shop for and own—but they lack information on why people buy the stuff they do. What gets folks staring at a shelf to “The Moment of Truth” (in P&G parlance) when they decide to make a purchase? The buying data alone cannot tell us.

Conversational Affinity: What about what people talk about online? Radian6 (Salesforce), Crimson Hexagon, and others really dig into social conversations and can provide tons of data that brands can use to get a general sense of sentiment. But this data, alone, lacks the lens of behavior to give it actionable context.

Social Behavioral Affinity: Finally, what about the actions people take in social environments? What if we could measure not just what people “like” or “follow” online, but what they actually do (like post a video, tweet a hashtag, or engage with a fan page)? That data not only covers multiple facets of consumer affinity, but also gives a more holistic view of what the consumer is engaged with.

Adding social affinity data to the mix to understand a consumer can be a powerful way to understand how brands relate to the many things people spend their time with (celebrities, teams, books, websites, musicians, etc.). Aligning this data with viewing, buying, and conversational data gets you as close as possible to that holistic view.

Let’s take an example of actionable social affinity in play. Say Whole Foods is looking for a new celebrity to use in television and online video ads. Conventional practice would be to engage with a research firm who would employ the “Q Score” model to measure which celebrity had the most consumer appeal and recognition. This attitudinal data is derived from surveys, some with large enough sample sizes to offer validity, but it is still “soft data.”

Looking through the lens of social data, you might also measure forward affinity: how many social fans of Whole Foods expressed a Facebook “like” for Beyonce, or followed her account on Twitter? This measurement has some value, but fails at delivering relevance because of the scale effect. In other words, I like Beyonce, so does my wife, and so does my daughter . . . along with many millions of other fans—so many that it’s hard to differentiate them. The more popular something is, the broader appeal and less targetability that attribute has.

So, how do you make social affinity data relevant to get a broader, more holistic, understanding of the consumer?

Obviously, both Q Score and forward affinity can be highly valuable. But when mixing viewing, buying, and listening with real social affinity data, much more becomes possible. The real power of this data comes out when you measure two things against one another. Sree Nagarajan, CEO of Affinity Answers, explained this mutual affinity concept to me recently:

“In order for the engagement to be truly effective, it needs to be measured from both sides (mutual engagement). The parallel is a real-world relationship. It’s not enough for me to like you, but you have to like me for us to have a relationship. Mapped to the brand affinity world, it’s not enough for Whole Foods fans to engage with Beyonce; enough Beyonce fans have to engage with Whole Foods (more than the population average on both sides) to make this relationship truly meaningful and thus actionable. When true engagement is married with such mutual engagement, the result is intelligence that filters out the noise in social networks to surface meaningful relationships.”

As an example, this approach was recently employed by Pepsi to choose Nicki Minaj as their spokesperson over several other well-known celebrities.

What else can social affinity data do?

Brands can use social affinity data to decide what content or sponsorships to produce for their users. Looking at their users’ mutual affinity between the brand and music, for example, might suggest which bands to sponsor and blog about.

A publisher’s ad sales team can use such data to understand the mutual affinity between itself and different brands. A highly correlated affinity between activated social visitors to GourmetAds’ Facebook page and those who post on Capital One’s Facebook page may suggest a previously unknown sales opportunity. The publisher can now prove that his audience has a positive predisposition towards the brand, which can yield higher conversions in an acquisition campaign.

What about media buying? Understanding the social affinity of fans for a television show can produce powerful actionable insights. As an example, understanding that fans of “Teen Wolf” spend more time on Twitter than Facebook will instruct the show’s marketing team to increase tweets—and post more questions that lead to increased retweets and replies. Conversely, an Adult Swim show may have more Facebook commenters, leading the marketer to amplify the effect of existing “likes” by purchasing sponsored posts.

Keyword buying is also interesting. Probing the mutual affinities between brands and celebrities, shows, music acts, and more can yield long tail suggested keyword targets for Google, Bing/Yahoo, and Facebook that are less expensive and provide more reach than those that are automatically suggested. As an example, when “Beavis and Butthead” re-launched on MTV, Google suggested keywords for an SEM campaign such as “Mike Judge” (the show’s creator) and “animated show.” Social affinity data suggested that socially activated Beavis fans also loved “Breaking Bad.” Guess what? Nobody else was bidding on that keyword, and that meant more reach, relevance, and results.

I believe that understanding social affinity data is the missing piece of the “360 degree view” puzzle. Adding this powerful data to online viewing, buying, and social listening data can open up new ways to understand consumer behavior. Ultimately, this type of data can be used to generate results (and measure them) in online branding campaigns that have thus far been elusive.

Want a full view of the people who are predisposed to love your brand? Understand what you both mutually care about through social affinities—and measure it.

Even though programmatic RTB has seen the lion’s share of venture capital funding and an enormous amount of innovation, RTB buying only accounts for 20%-30% of all digital media dollars. The real money still flows through the direct buying process, with agencies spending up to 400 hours and $50,000 to create the typical campaign, and publishers burning through 1,600 hours a month and 18% of their revenue responding to RFPs. What a mess….and an opportunity.

Everybody’s battling for a slice of that direct sales pie, and the game is all about helping buyers and sellers automate the manual processes that drive almost 80% of transactional value.

The Holy Grail for both sides is a web based, connected platform that will enable planners and sellers to thrust aside Excel, and start to transact business in the cloud. Although a number of companies have tried and failed to deliver on the promise of workflow automation, the time seems ripe for true adoption, as agencies are being challenged by their clients to create the same programmatic efficiencies across all media channels that they have embraced with RTB. As we speak, winners and losers are being selected, so let’s look at the landscape.

When you look at all of the companies providing a slice of the end-to-end workflow just in digital media execution, it’s hard to imagine that there can be “one system to rule them all” or a true “OS” for digital media. Yet, the dream is just that: An end-to-end comprehensive “stack” that handles media from research through to billing, and eliminates the many manual tasks and man hours involved in connecting the dots. But what are the realities? Let’s saddle up this unicorn and take a ride:

The End of the End-to-End Stack?

The notion of a single end-to-end “stack” for the digital marketer is a tough vision to execute upon. Build a system that has every little feature that a huge agency needs and you have effectively built something no one else can use. The flip side is building something so standardized that individual organizations find little value in it. The “operating systems” of the future that will win should enable agencies and marketers to leverage a standard operating system, but customize it with their own pricing, performance, and vendor data. This enables the efficiency of standardization while enabling data to provide the “secret sauce” that media shops need to justify their fees. More importantly, the modern operating system for media must be extensible, to allow for a wide variety of point solutions to integrate seamlessly. The right system will certainly eliminate a few logins, but must not limit the numbers of tools that can be accessed through it. That concept necessitates a highly modern, scalable, API-driven, web-based platform. It will be interesting to see how today’s legacy systems (which are exactly the opposite of what I have described) adapt.

Hegemon Your Bets

Several years ago, I wrote that the merger between Mediabank and Donovan may actually be a good thing—provided it offered more choice, flexibility, and open standards. Looking some three years later, I am not sure agencies have any more of that today. Like any other near monopoly, Mediaocean has a disincentive to open up its ecosystem because it invites competition. So time will tell whether their nascent “Connect” effort will become a way for agencies to quickly consolidate their “stack” around a flexible operating system—or if it’s just an integration tax for vendors (a revenue strategy quickly becoming known as the “Lumascrape”). After an IPO, the company will face enormous quarterly pressure for growth. It will be hard to raise prices on already stretched agencies, so publishers will be in the crosshairs. I smell “marketplace” and some monetization strategies around “programmatic direct” enablement for guaranteed media. And what about open standards? Despite years of work by the IAB, the standards and protocols for creating electronic ordering and invoicing are still very much in flux.

Connecting the Dots

More than anything else, the most exciting thing happening in digital media is seeing real programmatic connections between buyers and sellers for guaranteed media. After so much innovation in programmatic RTB (hundreds of vendors, billions in venture capital), we now have some amazing pipes that impressions can flow through. Unfortunately, this has largely been limited to lower classes of inventory and focused almost exclusively on the DR space. Creating the same programmatic efficiencies for “premium” brand-safe inventory is now starting to happen. Whether it comes from new “programmatic direct” pure play technologies, or happens through the RTB pipes, it will not happen successfully without transparency. That means giving publishers control over their inventory, pricing, and what demand partners can access their marketplaces. Will these connections thrive? Not if vendors charge network-like fees, arbitrage media, or don’t provide transparency. Will the endemic fraud in programmatic RTB push more transactions outside the RTB pipes? I think so, and a lot of publishers (see Yahoo/AOL/Microsoft deal) are betting that there are better ways for buyers to access their inventory.

Time for Real Time

Look at all the RTB players who want a piece of the guaranteed action. Three of them (Rubicon, Appnexus, and Pubmatic) will IPO soon, and be under tremendous pressure to increase revenue, margins, and continue to innovate and find new markets. When international expansion stops providing double-digit growth increases, then it’s time to look toward new streams of demand generation—namely, the 80% of deals not currently flowing through their pipes. Those pipes have been engineered for real-time bidding, but guaranteed deals are neither real-time nor bidded. Can they innovate fast enough to provide real value between buyers and sellers? Can they apply years of innovation in DSP and SSP tech to the more prosaic problem of workflow automation? Probably, but there are still business model issues to work out. Most of these companies have put a stake in the ground for either publishers or marketers, and a transactional platform must be agnostic to sit in the middle. It will be interesting to see how new offerings are received in the marketplace.

As the Chinese curse says, “may you live in interesting times.” Indeed, the past several years of ad tech has been nothing but interesting, but the real action is just starting—and it’s taking place in what was the most uninteresting field of workflow automation.

I was recently talking to the Chief Digital Officer of a large agency that does a lot of digital media buying. He has been working closely with a number of software providers to standardize his operations on a media management system. Getting all his vendor information, order management, and billing information has been a huge undertaking. Apparently, half the battle at an agency is getting paid (getting paid in less than 120 days is the other half)!

We were talking about some of the upfront processes behind putting together a media plan, which were mostly manual: putting the actual plan together in Excel, trading e-mails back and forth with vendors in the RFP process, trafficking ad tags, collecting screenshots, etc. Wouldn’t it be valuable if computers could streamline much of that work, and connect buyers and sellers together more seamlessly?

He agreed that it would truly transform his business, but accepted much of that manual work as part of the cost of doing business (paid for, incidentally, by his clients). The real way to transform his business, he said, was to answer the following questions. If “programmatic direct” technologies simply nailed down these four things, the payoff would be enormous. I paraphrase his answers below:

How much should I buy? “I basically know that I am going to have AOL, Yahoo, Facebook, and GDN on almost every plan. For my more vertical clients, in auto for example, I also know 95% of the sites and networks I am going to be on. Sure, I use research tools to validate those recommendations to my clients, but media discovery is not a huge pain point. Where we struggle is answering the question of media investment allocation. Should I spend 30% of my budget with Facebook? 40%? I really don’t know, and often don’t have the right mix until the campaign is nearly over. It would be great to have some business intelligence built into a system that recommended my guaranteed media mix programmatically.”

What should I pay? “I also have a pretty good idea what things cost, thanks to the RFP process. When you RFP 40 publishers in a vertical, you find out pretty quickly what your best pricing for guaranteed media is, and you can leverage that information to insure you are giving your clients competitive rates. Unfortunately, it feels like we go through this exercise every time on every RFP. We have the historical pricing data, but it’s all over the place in spreadsheets—and often in the planner’s heads. It would be great if this information was in the same place, and if a system could make pricing recommendations up front in the process, which would also shorten the negotiation process with publishers.

Why am I recommending this? “The biggest thing we struggle with is justifying our media choices to our clients. When we present a recommendation, often we are asking our client to invest hundreds of thousands or even millions in an individual vendor. My deck has to have more in it than basic audience information. I have to talk about the media’s ability to perform and hit certain KPIs for the price. It would be really useful to have recommendations come with some metrics on how such placements performed historically, or even some data on how other, similar, investments moved the needle in the past. Right now, getting to that data is nearly impossible, and usual resides with your senior planner in the account. The other obvious problem with that is employee turnover. My best planners, along with everything they’ve learned over two or three years walk out the door along with my data and relationships. The right system should store all of that institutional knowledge.”

You need that when? “The other thing a system can help with is speed to market. Publishers hate it when we ask them for huge, innovative proposals—in 24 hours. The reason we do that is because our clients ask us for amazing and innovative media recommendations in 48 hours. The pressure to deliver plans is huge, and you can easily lose large chunks of business by reacting to such requests too slowly. What programmatic direct technology may be able to help with is giving planners access to tools that compress the pre-planning process down, and enable agencies to deliver thoughtful, data-backed recommendations out fast—and at scale.”

Especially for larger agencies, programmatic direct technology has to be more than just workflow efficiency tools and automating the insertion order. (Although that has to come first). The next generation of programmatic efficiency or guaranteed media has to include serious business intelligence tools that can solve the “how” while simultaneously answering “why.”

Well, at least it’s not the “year of mobile” again. Or, maybe it is. After several days of media investment banking conferences (Gridley and JEGI), I can reliably report that 2014 will be “the year” of many uber-trends ,some of which will enrich the M&A bankers who have a focus on the increasingly frothy ad technology and marketing space. Here are five memes to consider:

“Mobile First”

If you were to believe every ad tech panelist, you might be inclined to throw your laptop in the East River. Apparently—despite desktop only slightly starting to lose overall time-spent share to mobile on a year-over-year basis—nobody is developing ad tech solutions for the desktop anymore. Everyone is “mobile first,” meaning that they are writing code for tablet and mobile phone browsers and apps before developing solutions for the poor laptop or desktop computer. Of course, mobile devices are showing explosive growth, and clearly where the majority of consumers’ time will be found (as evidenced by the 8 of 10 people at my conference table multitasking during the eMarketer presentation which laid out the mobile data). This might be only a slight exaggeration when it comes to mobile eCommerce, which is trending to dominate the vast majority of online sales transactions in just a short time. Also, in case you missed this, it is now passé to call “mobile” “mobile.” Companies are so hip to the growth in portable digital devices that they just talk about “reach” rather than distinguishing between “tablets” and “smartphones.” You know it’s really the “year of mobile” when it’s too lame to talk about.

“No Cookie, No Problem”

Guess what? Nobody is worried that cookies are going away. Again, if you spend all of your time in conference ballrooms listening to panelists, you naturally understand that cookies are a thing of the ancient past, rather than the data currency without which 80% of Lumascape companies could not credibly operate. In fact, if the cookie disappeared tomorrow, ad tech players would simply go with a “statistical ID” or another cool sounding identification technology that is being invented somewhere. I am really glad that no one is particularly worried but—hearing this meme several times over the past week—I would be interested in how many platforms and ad networks have developed and deployed data technologies that enable them to do audience targeting at scale without cookies. What I think the reality of the situation might be is that cookie technology is replaceable, but if legislation changes suddenly or Google Chrome decides to switch things up, there could be huge trouble in Luma land. So much value destruction in so short a period is just something not fun to talk about at M&A conferences.

“Stack”

The idea of the “technology stack” is not new for 2014, but what has changed is that tons of point solutions that were funded in 2008 are still unprofitable, their VCs are at the end of their fund lifespans, and it’s time to find an exit. That means someone unprofitable point solution can either become a part of another’s “stack” or everyone can take their toys and go home. The problem with everyone wanting you to have a “stack” is that they are expensive to build and also expensive to license via SaaS. Small players cannot afford a “stack” and the big players already have them. That dynamic is going to create a ton of M&A activity in 2014, as vulnerable point-solution providers, some with excellent technology, succumb to larger integrators. As repeatedly pointed out, the biggest players in the marketing space (IBM, Adobe, Salesforce, etc.) represent the vast majority of M&A dollar volume, all of which has gone towards augmenting “stacks”—and it doesn’t look like they are going to be done anytime soon. There are a lot of good engineers that aren’t going to exit big at their point solution company, and may be ready for a comparatively cushy work life in the bosom of corporate behemoths that offer unlimited Mountain Dew and Skittles in the company snack room. Look for lots more M&A, and much of it “aquihire” focused.

The Funnel is Dead…It’s Now the “Customer Journey”

Everyone now has to have an “omnichannel-capable programmatic offering.” That’s the one parked right next to my Unicorn. Not that the instinct is incorrect—the proliferation of screens means that marketers have to reach people along their “consumer journey.” It’s no longer a trip down the sales funnel, but a twisting landscape where the consumer pushes you information through various social interactions. The smart marketer has to be ready at the drop of a hat to deliver perfect, personalized messages into the consumer’s smartphone at the “moment of truth” before a purchase—and, at the very least, be prepared for various “Oreo” social media moments that can create “earned” media at scale. Sounds like marketers may actually start to miss the old “AIDA” funnel!

“Sutton Pivot”

One of 2013’s memes was the notion the “Sutton Pivot,” or running where the display money is—namely, the 70% of digital dollars that get transacted through the RFP channel. That’s where we get to complain endlessly about funding the “23 year old media planner” with “sneaker parties.” David Moore remarked at the recent JEGI conference that “50% of the cost of a campaign” went into the complexity of planning and delivering it. That sounds like a lot, but might be only a slight exaggeration. Everyone wants everything more programmatically, but the problem is that publishers haven’t quite given up yet. They are still keeping the premium inventory to themselves and out of the exchanges. “Programmatic everywhere” may become a reality…in five or six years. But old habits (and buying methodologies) die hard. In the meantime, everyone with a “platform” is going to try and figure out how to automate the inefficient buying process and try and get some of that 70% flowing through a system that creates a nice “percentage of spend” platform fee. 2014 will see this trend accelerate.

Happy New Year!

Every one of these memes will produce a ton of innovation, lots of M&A, a good deal of mid- to senior- level hiring, and plenty of bankers fees, so don’t worry! 2014 looks like a great year for ad technology!

“80 percent of the publishers getting an RFP don’t even stand a chance.” – Doug Weaver, Upstream Group

Direct mail is an amazing thing. It costs something like $750 CPM to put a glossy catalogue in the mail, but somehow direct marketers make those numbers work. Mailing lists are constantly optimized to make sure they hit the right houses, fresh lists acquired to create new demand, and non-performing lists ruthlessly culled if they don’t meet certain KPIs. Direct marketers actually can tell just how much money a mailing will produce in sales.

Contrast that with a banner campaign, in which “good” performance means a 0.05% click-through rate, 40% non-viewable inventory, and fairly dim transparency. Some of the greatest companies in the space, newly public and boasting hundreds of millions in run rates, are still challenged to justify spending to their marketing clients. Thankfully, last click attribution hasn’t gone anywhere. I recently overheard a marketer at a conference saying that 70% of clicks on her last campaign with a big, popular “platform” came from Yahoo Mail subdomains. It doesn’t take a genius to figure out that the marketer’s e-mail program was creating sales, but the fancy platform’s banners were making sure they were “last viewed” before the purchase.

So, how to get display advertising more like direct mail?

It must start with procurement. Marketers should be able to tell how much the media costs, who will view it, and who to buy it from. Unfortunately, unlike almost every other form of media on the planet, that doesn’t exist today for the digital marketer. Marketers can name their price in the programmatic RTB channel, but if they want access to directly sold inventory (making up as much of 70% of all digital media spend today), they need to purchase via the “transactional RFP” process.

I don’t know whose fault it was, but publishers didn’t help themselves when they decided to hide pricing information from agencies. With an endless supply of inventory (some 5 trillion impressions per month, according to Eric Picard), banner sales has always been a bit more art than science. Buy 1,000,000 homepage impressions at $20 CPM, and I’ll throw in 5,000,000 “ROS” impressions. Presto! You get a reasonable eCPM of just over three bucks. Everybody’s happy….except for publishers. In the long run, such practices devalue their inventory.

Media prices are still opaque in the transactional RFP channel, and agencies like it that way. In order to get basic pricing and availability information, they send out “requests for proposals,” which send publisher sales teams scrambling. According to recent research by Digiday and Adslot, publishers spend an average of 1,600 man hours a month on RFPs, and 18% of their revenue churning through RFPs that have an average “stick rate” of about 25% (campaigns that will deliver the contracted amount). Ouch! A lot can happen in 1,600 hours.

Peter Naylor, the IAB’s Publisher in Residence, speaking to publishers at a recent conference summed it up nicely when he said, “Agencies take the information they receive in RFP’s to get a view of the market.” In other words, agencies get access to all the pricing information, and publishers are left to wonder who they are competing with—and at what price.

Despite this, agencies would also like to see this procurement methodology perish also. They want to buy impressions at scale, control the price they pay, and be able to “out-clause” on demand. Programmatic RTB offers all of the above—but only on lower classes of inventory. New programmatic direct technologies seem to be the answer to the problem of transactional RFPs. Whether they leverage existing RTB pipes (private deals) or are API-driven solutions connected to the publisher’s ad server, more and more higher-class inventory is starting to find its way to programmatic channels. That’s a good thing. Sure, there will still be RFPs for sponsorships, but sooner or later, all commoditized banner inventory (including “mobile” and video) will likely be purchased programmatically.

The question for publishers is whether or not they are going to take a part in deciding what the next stage of digital media procurement looks like. Will it still be driven by the demand side, or can publishers have a bigger seat at the table, and help build the process by which they expose and sell their “premium” inventory?

The RFP is dying, and publishers may applaud the last breaths of an over complex and inefficient process. But they should be careful of what may take its place.

An interview with Econsultancy’s Monica Savut and me, on the recently published programmatic direct whitepaper.

Econsultancy: Why now? In other words, why has this “programmatic direct” trend been on the radar lately? What’s driving all of the conversation the space?

Chris O’Hara: It’s really something my boss Joe Pych calls the “Sutton Pivot,” inspired by the famous thief Willie Sutton who robbed banks “because that’s where the money was.” Over 70% of digital display dollars are transacted in a very manual way today. Despite all the LUMAscape hype over RTB, most of the digital money still gets transacted through the request-for-proposal (RFP) process. Everybody wants a piece of the action, hence the “Sutton pivot,” in which all the ad tech companies are running to try and provide automation technology for directly sold deals. It’s actually a good thing. Today’s process for buying guaranteed digital media can take over 40 steps and suck up over 10% of media budgets just in man hours.

Q: The concept of “programmatic direct” or “programmatic premium” is a relatively new phenomenon, but it’s really just about automating the buying process for digital media, right? What makes it different from the automation happening in real-time bidding? What’s the difference?

A: Real-time bidding, or what we are starting to call “programmatic RTB” has been a real boon to the industry. We now have a set of “pipes” which connect demand- and supply-side platforms that make the digital media procurement process hugely efficient. Today’s systems are modern, cloud-based, scalable, and super low latency. We are seeing the type of liquidity and deal flow that happens in systems like NYSE and NASDAQ. That said, 70% of buying that happens in digital is neither “real time” nor “bidded.” It’s just two organizations trying to make a deal. You need different technology to enable that kind of guaranteed transaction, and marketers are starting to wonder why they are paying so much in transactional costs to access higher classes of digital inventory. RTB proved that efficiency can happen in digital, and now marketers want faster and more efficient access to more than just remnant inventory.

Q: You say that agencies have a “perverse incentive” to embrace efficiency in buying. It would seem counter to everything that is happening in the programmatic space at the moment. How do demand side business models need to adapt for programmatic direct to become a reality?

A: Agencies make money when plans take 400 hours to create. Manually trafficking line items in an ad server, and cutting and pasting publisher insertion orders pays the bills for agencies who charge on a “cost-plus” basis. Digital media agencies have been operating that way for years: hire cheap, work the “23 year old media planner” hard, and earn a mark-up on their labor. Nothing wrong with work-for hire, but the RTB phenomenon—and marketers experience with easy-to-use programmatic platforms in search and social marketing—have changed the dynamic entirely. Agencies have to do more than heavy lifting now to survive. They need to hire fewer, smarter, people to leverage systems—and more great creative and analytical people to make sure they are driving digital messages that inspire—and meet KPIs. The days of getting paid to traffic ads in MediaVisor are over. That’s a big time cultural change for agencies. A lot of shops won’t survive the transition, and that’s a good thing.

Q: What are some of the things—beyond cultural change—that need to happen to create this new era of programmatic direct efficiency? What’s missing?

A: We tend to think of digital as this highly advanced form of marketing, but it’s really the most backwards. Direct mail costs something like $750 per thousand (CPM) to put a catalog in the mail—and marketers like LL Bean make that number work consistently. Digital struggles to make $10 CPA goals work on $5 products. That’s really lame. Part of the problem is the lack of basic information available to the marketer. If I want to buy a direct mail list, I can find out how many folks in the list live in San Francisco, and have purchased a product by credit card in the last month. I can find out how much it costs to by that list—and who sells it. Until recently digital media has had no such directory. Not only that, but the industry lacks even the most basic set of electronic ordering protocols, that can enable systems to understand each other in electronic transactions. The good news is that more work has occurred on this front in the last two weeks than has happened in the 5 years the IAB has been promoting “eBusiness” initiatives. Look for some significant announcements in this area soon.

Q: Who benefits most from adopting programmatic direct strategies? Publishers? Agencies? The marketers themselves? Are there winners and losers if this new tactic sees adoption at scale?

A: It’s easy to say that “everyone’s a winner” with programmatic direct adoption at scale, but that’s not entirely true. I think publishers are the big winners, because they are starting to take some control back over the procurement process from the demand side. I think longer tail sites that depend on RTB revenue streams will continue to be able to get access to demand at scale through RTB systems, and still get their AdSense money. But what really excites me is seeing high quality publishers that own high quality real estate on category specific properties finally get more control over pricing and partner selection. This will be even more critical as publishers expand their offerings cross-channel, into video. Publishers need a programmatic way to sell their higher classes of inventory, and not be so dependent on prevailing procurement methodologies which overvalues biddable, commoditized inventory. Agencies who value higher class inventory also win, of course.

A: Everything digital will be bought “programmatically” in 5 years. Some will be RTB display, and some will be display, native, and video inventory purchased through “programmatic direct” platforms. Addressable television, digital out-of-home (DOOH), and other channels will also factor in. Once we can get a true unique identifier that makes sense from a technology and privacy standpoint (big question, obviously), then marketers will really be living in programmatic heaven.

Q: You’ve been working in the “programmatic direct” space for a long time (staring at TRAFFIQ in 2008), and yet there seems to be fairly little adoption of the concept among agencies. Are you crazy? Why keep doing it? Will there be a big payoff in the end?

A: Change is really hard, especially when the pace of change is as rapid as in digital ad technology. When I was on the publisher sales side, there was always something that bothered me about getting a $200,000 insertion order for digital advertising through a fax machine. That stuff still happens today. Ultimately, I so believe that true process automation will happen in digital media, and that we can free people in the space to stop doing a lot of manual grunt work, and start being truly creative. I was watching a documentary the other night, and an engineer was talking about why he loved his job. He said he spent the last three years building a bridge that eliminated 10 minutes from the commute for some 20,000 people a day. “I saved people over 50,000 days of productivity last year,” the engineer explained, adding, “I wonder what those people are doing with all that extra time.”

There are a lot of young people who go into an agency thinking that they are going to help make the next kick-ass viral ad, but they end up working until 10 o’clock at night pasting line items into an ad server. I really think that, if we can change that, great things will happen.

Lately, I have been working on a whitepaper about the “programmatic direct” phenomenon. Part of the research involved surveying a bunch of influential people in the space, and asking them where they thought this new buying methodology was in terms of adoption. Their answers kind of surprised me.

If “programmatic direct” was a baseball game, we are in the top of the second inning.

The game has basically just started, and a few balls have been put into play, but the action is just getting started—and the big sluggers have yet to step up to the plate. If you are a regular AdExchanger reader, you would be justified in thinking that programmatic direct was quickly gaining steam by progressive agencies and publishers. After all, there has been a good deal of hype surrounding the idea of enabling programmatic access to higher classes of inventory, and it seems like almost every ad technology player in the display space is getting into the game.

Sure, some real innovations are happening in programmatic RTB that are enabling private marketplace transactions. Initiation-only auctions and fixed rate deals inside of exchanges are only the tip of the iceberg, though. New web-based technology and advanced ad server APIs are starting to provide real process automation—the tools that will make it easier to buy and sell the 70% of inventory currently procured through the “transactional RFP” process.

However, there are a few major things that need to happen before “programmatic direct” can really take hold:

A Directory: It may sound strange, but one of the biggest failings of digital media has been the lack of a directory for buyers. In direct mail, you can look up how many people get the L.L. Bean mailing list, add all kinds of criteria (males of a certain age that have purchased with a credit card in the past three months), find out exactly what it costs, and who to buy it from. No such thing exists in digital media. Hence, the RFP process, where buyers have to go through hoops just to get a sense of pricing and availability. This simple act of discovery adds time and complexity to every transaction. Today’s programmatic direct systems are being built from the ground up—starting with good information, and also with dynamic pricing and availability information thanks to API connections to DFP and other publisher ad servers.

Standards for Electronic Ordering: Another obvious thing that needs to happen before real process automation can happen in digital is that a set of standards have to be agreed upon. The IAB has known this since 2008, but five years later the “eBusiness Task Force” (now called the “Digital Automation Task Force”) seems no closer to its original mandate. Its stated mission: Updating the XML schema and implementation testing for the electronic delivery of digital advertising business document.” Those documents include Requests for Proposals (RFPs), insertion orders (IOs), and invoices—documents that must be standardized in order for adoption of programmatic direct buying to occur at scale. However, there is urgency like never before to get such standards implemented, and a source close to the action says that “we will see more movement in the next nine months in standards and protocols than has happened in ten years.” Let’s hope so. The wide adoption of a common set of standards and protocols opens up the door to the electronic IO—the key to achieving scale in programmatic direct.

Culture Change: While a directory can be created and standards adopted with lots of hard work, those things are actually easier than the real key to programmatic direct adoption: culture change among agencies and publishers. Agencies must leverage technology to empower the “23 year old media planner” and give them a reason beyond sneaker parties to go to work. Technology will unleash their creativity and get them focused on solving real problems for clients. Likewise, publishers need to escape the “$200,000 a year salesman,” with his accompanying high T&E and schmoozy selling style. Publishers need data-driven sellers that understand how to drive programmatic adoption, and can sell based on the new “media investment” paradigm happening at agencies—understanding tactically how to spread digital dollars across a broad portfolio of channels. Agencies now they cannot remain stuck with the current cheap labor model. Publishers understand that they cannot keep their higher classes of inventory outside of programmatic channels. Change is hard, but it’s already here.

About a year ago, I said that 2013 would be the year of programmatic direct. It turns out that 2013 has been the year of programmatic direct hype, and a ton of valuable behind-the-scenes work on the technologies that will drive it in the future. But unlike the perennial “year of mobile” programmatic direct will become a reality quickly if some of the above building blocks come together.

When you are selling anything, it’s really easy to get caught up in pitching the benefits of your product, and ad technology is no different. Some of today’s new programmatic direct marketing solutions promise to change the very nature of how media buyers and sellers spend their time. Demand side systems are focusing on replacing Excel and e-mail with web-based, centralized systems that take the manual grunt work out of buying. Supply-side systems are tying into publisher ad servers to help create more streamlined access to inventory, without the hassles of secure it via paper insertion orders. While it’s easy to focus on all of the amazing efficiency benefits offered by today’s web-based solutions, it’s also critical to remember to ask your client what’s important to them.

On a recent sales call to a large agency, my old-school sales training kicked in. After showing off all of the neat bells and whistles of my software, I asked the company’s Chief Digital Officer why my ad technology was interesting to his agency. What he said was simple, but illustrative: “Our clients don’t ever come to us and ask what kind of tools we are using to do our jobs. They really couldn’t care less. But they do come to us and ask for huge media recommendations, due within several hours. And they definitely want to know why we are recommending what we are recommending.”

This made a lot of sense. Nobody wants to see the sausage get made, but it had better taste good once it’s cooked. Over the course of our conversation, I took away a few key nuggets that would be valuable for any technology company looking to sell programmatic solutions to marketers and publishers alike.

Clients Care about “Why,” not “How”

This statement is true for both agencies and publishers. An agency’s big client doesn’t care what tools the agency uses to create and execute its media plans (as long as the cost is transparent and within reason), but it does want to understand the overall strategy, rationale behind its vendor choices, and (of course) obtain measureable results. On the publisher side, the clients acquiring the inventory don’t care what kind of tags or datasets produce a targetable audience—they just want the publisher’s “auto intenders” to see ads for their cars.

In both cases, the “how” doesn’t matter—nor should it. Programmatic done right hides the way the sausage is made, and offers simple controls over complex processes. The best companies in the space will be able to turn a sound engineer’s control board (thousands of knobs and switches) into Avid’s Pro Tools. This is particularly important when trying to scale an organization; it is the difference between trying to turn dozens of people into technicians and having a technical system that everyone can use with little training. Companies with the right, scalable technology can grow…and grow fast.

For my agency client, being able to tell his client how he selected the programs on his media recommendation was critical. Using software that could help his planning team make choices based on past performance, alignment with demographic data, or even the client’s first party data was the key. When you have 40 20-something media planners spending millions of dollars, data-driven guidelines are essential, along with the platform to generate them. Likewise, on the publishing side, publishers need to tell their agency clients why certain programs were recommended, and have a systematic way to put together inventory packages that will perform well enough to avoid the dreaded out-clause.

Speed Matters

Another thing the agency CDO told me was how important speed was. They say efficiency doesn’t sell, but when your client is looking for a thoughtful media recommendation in two hours, being able to deliver a plan you can justify means having the tools to move fast, and move smartly. “It’s hilarious to me that our clients ask us for a completely unique, groundbreaking idea—at 6:30 PM—and expect something the next day.” This rolls down the hill to publishers, who are ultimately asked to help contribute to such plans on even shorter notice. Although there’s no cure for overly demanding clients, there is starting to be new programmatic direct solutions that help take some of the viscosity out of the transactional RFP funnel, increasing the speed to which proposals can come to market.

No Data, No Strategic Advantage

“Big Data” is all the rage, but even relatively small data can be the key to success when it comes to digital media buying and selling. “We know that every plan is going to have Facebook, AOL, and Yahoo on it. Access to their inventory and securing it is not the problem,” the agency CDO told me. “The real problem is, how do I know how much to allocate to each? What should my media channel mix be? That’s what we struggle with. Oftentimes, it comes down to gut instinct.”

Right now, data that can help with making those allocations is hidden all over the place: Excel-based media plans and performance reports, ad serving data that’s hard to report on, audience verification data from measurement tools, and in the brains of media supervisors. This structured data, centralized in the right place, can mean the difference between creating accessible insights—or being just another 10 gigabytes sitting on a computer’s hard drive. Agencies should be able to query all of the data available to them programmatically, and offer media choices chosen from algorithms that get smarter every time a campaign is run. Likewise, publishers should be able to systematically recommend inventory packages based on past performance, demographic and contextual relevance—and even whether or not they were re-purchased over time.

Programmatic direct solutions are starting to bring the type of data-driven efficiency once only found in RTB to both advertisers and inventory owners, creating a more “bionic” dynamic, where humans leverage technology to be better, faster, and smarter.

NextMark today announced the creation of Bionic Advertising Systems, a new division focused on delivering technology that streamlines digital advertising workflow for digital marketers, their advertising agencies, and publishers.

“The new Bionic brand represents our philosophy of delivering advertising technology that combines the strengths of humans and machines,” remarked Joe Pych, CEO of NextMark, and co-founder of Bionic. “Over the past few years, there’s been a battle of man versus machine in digital media. Neither side is winning. Instead of man or machine, the best ‘systems’ of the future will be a combination of both. The recent announcements by AOL,Yahoo!, and Microsoft around Programmatic Direct validate this belief and heralds a new age in digital advertising: the Bionic Age. As the name implies, our new Bionic unit is 100% dedicated to delivering solutions for this new era in digital advertising.”

Launched today, Bionic Advertising Systems will encompass NextMark’s solutions for digital advertising, including the latest Programmatic Direct technologies. Bionic’s software automates the mundane processes of digital media planning, buying, and ad operations. It frees media planners, buyers, and sellers to spend their time on higher-value tasks. It enables digital media planners to find advertising opportunities, gather information, create and send requests for proposals, negotiate with publishers, build media plans, execute orders, and implement their campaigns with the click of a button. With its modern API-driven architecture, it integrates with popular agency tools such as Doubleclick, MediaMind, and comScore. It’s currently integrating with leading sell-side Programmatic Direct technology providers Adslot, iSocket, and Yieldex. Bionic’s Digital Media Planner aims to tie together the many disparate systems used in digital advertising, giving them a single interface that simplifies the way they develop and deliver media plans.

“’Bionic’ is such a great concept for the digital media industry,” added Chris O’Hara, the business unit’s co-founder and Chief Revenue Officer. “A lot of companies in the space think that algorithms and robots are the answer. We know human creativity can be unleashed by automation, and that digital advertising works best when people are empowered by technology.”

Currently, more than forty advertising agencies are using the Bionic Digital Media Planner to create and execute their media plans. More than 900 publishers and networks are using the Bionic Digital Ad Sales System to promote more than 9,000 premium digital advertising programs—the largest directory of its kind, which also powers the IAB’s Digital Advertising Directory.

Recently, I had a cup of coffee and a macaroon with a guy named Christopher Skinner. Christopher has spent the last dozen years or so running a company called MakeBuzz after selling his old company, Performics, to Doubleclick. Lately, he has been keynoting some of Google’s “Think” conferences. Google likes what his company does for them—after using his software, marketers start to spend a lot more money on branded display. In other words, instead of just loading up on keywords and obvious AdSense display inventory, marketers are leveraging data that says digital display works to build a brand’s customer base. Without getting too specific, the software offers geo-targeted media recommendations that aim to optimize profits in specific areas—helping a company go from selling 100 widgets a month in Poughkeepsie to 150.

When I asked what the secret sauce was, I was surprised at the answer. Christopher drew me something on a napkin that looked like this:

The problem, he told me was that marketers weren’t striking the right balance between branding and direct response, and focusing too much on capturing customers they already had. In other words, if your business was like a lawn, and the profits were grass clippings, most folks were spending too much time cutting and not enough time fertilizing. To get the grass to grow, you want to fertilize it (branding) and get plenty of new blades to pop up as often as possible. When you cut it (direct response), you want to do so in a way that ensures it won’t get burnt, and lose its ability to sustain itself. It’s a delicate balance between growing demand through branding, and harvesting those efforts through direct response.

Looking at his crudely drawn chart, the line represents reach, going from a single user to the entire population. Most marketers stop 20% of the way through, and put all of their focus on their customer base through search and programmatic RTB display efforts—using data to ensure they are reaching the right “intenders,” but missing the opportunity to create new ones through branding. On the far right (dotted line), you have all the potential customers that are addressable; these users are still “targeted,” but so widely that hitting them with messaging is fraught with waste. This is the digital equivalent of advertising to “the demo” on television. Sure, it creates demand for BMWs, but only a certain portion of the audience has enough dough to afford a 5-series.

The simple message that many marketers continue to miss—either by focusing way too much on DR, or over indexing on untargeted branded efforts—is that a balance is critically important in the digital marketing mix. While it sounds simple to find the right balance, it actually requires a strong base of knowledge to execute properly. This is what I mean:

Measure Differently: Before you can understand the mix you need to achieve between branding and DR, you need to agree on a meaningful metric. Far too many digital campaigns are judged by three-letter performance acronyms that are proxies for success. Great CTR and CPA are positive signs—that you are doing all the right things to reach the audience you have already earned. They are poor indicators of your success in building new customers. Thinking holistically about your marketing efforts yields new benchmarks: If your company typically sell 200 widgets in the Upper West Side of Manhattan, why shouldn’t you be able to sell the same amount in San Francisco’s Nob Hill? In other words, how about using “profit optimization” as the primary metric? This requires a relationship with the advertiser that goes beyond the agency, and plenty of first-party data, which is why such simple yet effective metrics are not used frequently.

Spend More on Branding: Sometimes, what holds good marketing back is a reliance on known metrics. In another year, the banner ad with be 20 years old. While the banner ad ushered in an era of “measurability,” it also took marketers on a path to thinking that anything and everything could have its own success metric,and we went from a dependence on soft, panel-based, attitudinal metrics to today’s puzzling array of digital KPIs. Did Absolut vodka worry about CTR on its way to becoming the dominant liquor brand of the last quarter century? Or did they just design great packaging and put big beautiful ads on every magazine back cover they could find? At the end of the day, TBWA made a decent vodka into a great brand, and the only metric anyone ever worried about was case sales. They did it by spending LOTS of money on branding.

Find the Sweet Spot: Spending more on branding is obviously important for “growing the grass,” but not every product is one everyone can afford. While it made sense for Absolut to advertise to the broader population of adults in magazine, most marketers have a more limited audience and budget. Finding the sweet spot between branding and DR has a lot to do with knowing your potential customer and how they make purchase decisions. If you believe (as I do) that word-of-mouth is the most powerful medium, then it makes sense to apply as much granular targeting to a campaign—without restricting it with too much targeting data. Neighbors talk to and influence each other—and the Smiths and Joneses tend to chat on the soccer field about cars, vacations, and even the latest medical procedures. Your sweet spot is where you can faithfully blanket ads in a neighborhood or larger area that has a built-in predilection to purchase. It’s not a broad as city targeting, which wastes messaging on customers that can’t afford your products, and not so targeted as “intender” targeting, which limits your addressable audience to people who already love your brand.

Today, it seems like digital marketers are limiting their reach to their existing customers—spending lots of lower-funnel effort dragging “intenders” across the finish line, so they can attribute lower acquisition costs to their campaigns. Although the real customer growth is grown through branding efforts, most marketers are scared to open up the spigot and deliver large amount of impressions, and especially hesitant to migrate marketing to cookie-less mobile devices and tablets which are harder to target. But to grow customers, you need to introduce them to your brand—and find them where they live. When you water the lawn religiously, there is always plenty to cut.

I have been thinking about, and trying to solve, agency digital workflow problems since 2008.

Given the complexity of digital media, the variety of creative sizes, millions of ad-supported sites, and dozens of ad servers, analytics platforms, order management and billing tools, it goes without saying that the digital marketing stack has been hard for any agency to put together.

Recent research has tracked the immense level of complexity involved in digital media planning (more than 40 steps) and the tremendous expense involved in creating the actual plan (up to 12% of the media spend). It all adds up to a lot of manual work for which agencies are not willing to pay top dollar, along with frustrated agency employees, overbilled clients and a sea of technology “solution providers” that only seem to add to the complexity.

Media planning on the agency side is a big time suck. Yet some agencies are still getting paid for it, so it’s a problem that is going to get solved when the pressure from agency clients increases to the point of action, which I think we’re just now hitting in 2013.

But who is thinking about the publishers? Despite dozens of amazing supply-side technologies for optimizing programmatic RTB yield, there are only a few providers focused on optimizing the 70% of media dollars that flow through publishers’ transactional RFP channels.

DigiDay and programmatic direct software provider AdSlot and recently studied the transactional costs of RFPs. The sheer numbers stunned me. Here’s what one person can spend on a single RFP:

5.3 hours on pre-planning

4.2 hours on campaign planning

4.0 hours on flighting

5.3 hours on maintenance

3.3 hours post-campaign

That’s more than 22 hours – half a business week – spent creating a single proposal and starting a campaign, which, according to the study, has a less than 35% chance of getting bought and a staggering 25% chance of getting canceled for performance reasons after the campaign begins. The result is a 25% net average win rate. That’s a lot of work, especially when you consider how easy it is for agencies to lob RFP requests over the transom at publishers. On average, publishers spend 18% of revenue just responding to RFPs, which translates to 1,600 man-hours per month, according to the study.

So, we have a situation in which agencies, which are firmly in control of the inventory procurement process, are not only wasting their own time planning media, they are also sustaining a system in which their vendors are wasting numerous hours comporting with it. In short, agencies spray RFPs everywhere, and hungry publishers respond to most. The same six publishers make the plan every year, and a lot of publishers’ emails go unanswered. What a nightmare.

A Less-Than-Perfect Solution

To combat this absurdity, many publishers have placed large swaths of their mid-premium inventory in exchanges where they realize 10% of their value but avoid paying for 1,600 hours of work. The math isn’t hard if you know how agencies value your inventory. Publishers aren’t stupid. Inventory is their business, and most work very hard creating content to create those impressions. These days, every eyeball has a value. Biddable media has made price discovery somewhat transparent for most[CO1] inventories. Programmatic RTB is great, but not all publisher inventories[TH2] are created equal. A small, but highly valuable percentage will never find its way into an SSP.

Publishers will always want to control their premium inventories as long as they receive a greater margin after transactional RFP labor costs. Publishers who actually have strong category positioning, contextual relevance, high-value audience segments and a brand strong enough to offer advertisers a “halo” have to manage their transactional business so they can maintain control over who advertises and what they pay. This looks the year that demand- and supply-side software solutions may finally come together to solve the problem of “transactional RFP” workflow.

A couple of new developments:

Demand-Side Procurement Systems Are Evolving: Facing significant pushback from clients and seeing new and accessible self-service media buying platforms gain share, agencies are looking hard at tools to gain efficiency. Incumbent software systems like Strata and MediaOcean are modernizing, while new, Web-based tools are gaining adoption among the middle market. Suddenly workflow efficiency is all the rage and agencies that spend 70% of their money in the transactional RFP space want a 100% solution.

Supply-Side Direct Sales Systems Are Available: A few years ago, there were lots of networks and marketplaces for publishers to put inventory before going directly into exchanges. Many were more generous than today’s exchanges, but still offered low-digit CPMs and not much control over inventory. Now there are a variety of systems that plug directly into DFP and enable publisher sales teams to have real programmatic control over premium inventory. AdSlot, ShinyAds and iSocket are rapidly gaining adoption from publishers that want another premium channel to leverage, without giving up pricing control. To succeed, these publishers’ systems must be connected to the platforms that manage demand.

Who Put Peanut Butter Into My Chocolate? What is slowly happening, and will continue in a huge way in 2014, is that demand- and supply-side workflow solutions will come together. What does that mean from a practical standpoint? Planning systems will be able to communicate with ad servers, eliminating double entry work; ad servers will be able to communicate with order management and billing systems, eliminating even more duplicative work; and the entire demand side system will be able to communicate orders directly into the publisher workflow systems and ad server.

Simply put: Agencies will be able to create a line item in a media plan, electronically transmit an order to a publisher, which the publisher will electronically accept, and the placement data will be transmitted into the publisher’s ad server. A line item will be planned, and it will begin running on the start date. Wow.

That’s what we are starting to call programmatic direct. It’s a world with a lot less Excel and email, with thousands of hours that won’t get wasted on transactional RFP workflow for agencies and publishers.

Lately, I’ve been thinking a lot about the hourglass funnel. Most funnels stop at the thin bottom, when a customer “drops” out, having made the journey through awareness, interest, desire and action. After the “action,” or purchase, the customer gets put into a CRM to be included in more traditional marketing outreach efforts, such as calls, e-mails, and catalogue mailings. In the past, marketers often thought about how to turn customers into advocates, but couldn’t figure out how to do it at scale. Companies that were really good at multi-level marketing, like Amway, didn’t have easy-to-replicate business models.

Today, the situation has changed. Social-media platforms give marketers tools to engage customers in their CRMs and bring them back through the bottom of the funnel, turning them into brand advocates — and maybe even salespeople. This is why Salesforce has been snatching up social-media companies like Radian6 and Buddy Media, while Oracle bought Vitrue and Involver. These platforms can help get people talking about your brand– and, in turn, you get to listen to what they have to say. These platforms also can help you understand what it takes to get your customers to move from liking your page to actively sharing your content and to actually recommending your products and even selling them as an affiliate.

The ad-tech revolution of the last several years has supercharged our ability to drive people through this hourglass-shaped funnel. But instead of enabling this movement, we have instead – for the most part — focused on wringing efficiency out of reaching the customers we’re already very close to getting. For example, programmatic RTB makes it easy to bid on people in the “interest” layer, who behave like existing customers. Additionally, it’s a no-brainer to retarget those customers who have already expressed “desire” by visiting a product page or your website. And technology also makes it increasingly easy to invite customers already in your CRM to “like” your Instagram page, or to offer them incentives to “recommend” products through social sharing tools.

But what about the very top of the funnel (awareness) and the very bottom (advocacy)? Those are the two most critical parts of the marketing hourglass funnel, but the two least served by technology today. While we have tools to drive people through the marketing process more quickly or cheaply, technology doesn’t create brands or turn social-media fans into brand advocates.

However, the right strategy for both ends of this funnel can still boost awareness and advocacy by creating a branding vortex that is a virtuous circle. Let me explain:

Awareness

You can’t start a customer down the sales funnel without making he or she aware of your product or service. Despite all of the programmatic promise in display, technology mainly emphasizes reaching our known audience most efficiently. It simply hasn’t yet proven that it can create new customers at scale. That’s why TV still gets the lion’s share of brand dollars. Cost-effective reach, pairedwith a brand-safe, viewable environment, is what TV supplies.

In my opinion, the digital answer for raising awareness is starting to look less and less like programmatic RTB and more like video and “native” formats, which are more engaging and contextually relevant. Also, new programmatic direct technologies are starting to make the process of buying guaranteed, premium inventory more measurable, efficient and scalable.

Programmatic RTB advocates will argue that you can build plenty of awareness across exchanges, but it’s hard to create emotion with three IAB standard units, and there still isn’t enough truly premium inventory available in exchanges today to generate a contextual halo for your ads. New “native” display opportunities, video and tablet advertising are where branding has the biggest impact. Adding those opportunities to social tools, such as Twitter and Instagram, would help you leverage your existing brand advocates and amplify your message.

Advocacy

Great digital branding at the “awareness” level of the funnel not only helps drive potential new customers deeper into the sales funnel, but also can help engage existing customers. This amplification effect is extremely powerful. Old-school marketers such as David Sarnoff understood that folks make buying decisions through their friends and neighbors. He also understood that, when you’re trying to sell the next big thing (like radio), you have to leverage existing media (print). Applied to digital marketing, this simply means leveraging awareness media — TV, video and “native” advertising — to stimulate word-of-mouth advertising, which is still the most powerful type. By using Facebook and other social sharing tools, the effect of any campaign can grow exponentially in a very short period of time. This virtuous circle of awareness media influencing brand advocates, who then create more awareness among their own social circles, is something that many marketers miss when they lead their campaigns with data rather than with emotion.

Everything In Between

I’m not saying that marketers can simply feed the top of the funnel with great branding and ignore the rest. That’s not true at all; the middle of the funnel is important too. I think it’s relatively easy, nowadays, to build a stack that also helps support all the hard work that brands are doing to create awareness. Most large marketers reinforce brand efforts with “always on” programmatic RTB that targets based on behavior, and all brands employ as much retargeting that they can buy. Once customers are in the CRM, it’s not hard to maintain a rewards/loyalty program, and messaging to an existing social fan base also is relatively simple.

But marketers are making a mistake if they think that this kind of programmatic marketing can replace great branding. With so many different things competing for customers’ attention, capturing it for more than a second is extremely difficult, and the challenge is only going to get harder.

The Datalogix Effect

So what does all this mean for for ad technology? The best way to think about this is to look at the Datalogix-Facebook partnership. Datalogix’s trove of customer offline purchase data essentially enables brands to measure whether or not all their social-ad spending resulted in more online sales. A few studies have pretty much proven that media selling soap suds on Facebook created more suds sales at the local Piggly Wiggly. In fact, ROI turns out to be easy to calculate, as well as positive.

This type of attribution seems simple, but I don’t think you can overstate its impact. It’s the way we finally move from clicks and views to profit-optimization metrics such as those offered by MakeBuzz. And this method of tying online activity with offline sales is already having a vast impact on the ecosystem. It shows, beyond doubt, that branding sells product.

Getting the attribution right, though, means that brands are going to have to care about creative and content more than ever. It means big wins for video, “native” ad approaches, and big tentpole marketing campaigns. If quality premium sites can be bought programmatically at scale, then it may also mean big wins for large, traditional publishers.

It also likely means that many retargeters, programmatic RTB technologies and exchanges could end up losing in the long run. Don’t get me wrong: These technologies are needed to drive the “always on” machine that powers the middle of the funnel. But just how many DSPs and exchanges does the industry need to manage its commoditized display channel?

As marketers realize that they are spending money to capture customers that were going to convert anyway, they’re likely to focus less on audience targeting and more on initiatives to create new customers — and turn existing customers into advocates.

I recently sat through some great presentations on “programmatic direct” media buying at the recent Tech for Direct event in New York. With almost 70% of digital display dollars flowing through the negotiated (RFP) market, everyone wants to be in the game. One of the presenters, John Ramey of iSocket talked about what has happened to the advertising yield curve for digital display. This curve starts at the upper left corner with premium inventory capturing the highest CPMs, and is supposed to flow gently downward on the x-axis, towards the lowest value of inventory, ending on the lower right corner. A classic marketplace yield curve. In this world, ESPN can charge $20 CPMs for their baseball section, sites like Deadspin in the mid-tail can charge $7, and the networks and exchanges aggregating hundreds of sports blogs in the long tail can charge $1. Nice and fair, and rational.

This is not what has happened, though.

As Ramey correctly points out, we have a yield cliff now. This is world in which there are two types of inventory: The super-premium, which is hand sold directly for double-digit CPMs; and the remnant, which is sold via RTB on exchanges or surviving ad networks, often for pennies. In this world of the Haves and Have-Nots, there is no middle class of inventory—even though one could argue that $7 inventory on Deadspin might actually outperform its upscale cousin, ESPN. This inventory disparity we have created in the digital advertising industry has nothing to do with supply and demand, but everything to do with the process by which we transact.

Premium mid-tail buying is a great idea. Back in 2009, marketplace platforms like TRAFFIQ were bringing this innovation to the space, and enabling marketers to cherry pick and aggregate premium quality sites that could offer friendly CPMs and URL-level transparency. It’s not a new concept. In fact, I think premium mid tail buying is the canary in the coalmine for programmatic direct; when today’s technology can make it easy to put together a large array of guaranteed buys, and enable fast and easy optimization, then we will have succeeded. Here what was missing in 2009, and what we need to succeed today:

A Centralized Directory: You can’t buy stuff without knowing what’s available and how much it costs. Other media channels like direct mail have published prices for mailing lists, right down to audience targeting. You want to reach people who have bought something from the Cabela’s catalog in the last six months, and restrict the mailing to men only? No problem. You can find out what it costs, and who sells it. The digital display market needs to be organized in a directory, down to the placement level. You shouldn’t have to wait for an e-mail back from an RFP to find out what known inventory costs. That work is being done now, but has a lot more work to go through before it is comprehensive.

An Extensible Platform: Today’s API-driven technology makes it easy to enable buying directly into publishers’ inventory. A link into DFP means buyers can discover availability and start serving ads with a few button clicks. The problem is that agencies want a Single System to Rule Them All. So far, agencies have been stuck with installed, legacy systems that have more to do with billing and reconciliation than media planning and buying. Agencies want new, web-based ways to discover and buy great inventory, but they also want a system that plugs into their existing tools. They are not going to log into another buying system if they don’t have to. A system that can enable premium mid-tail buying at scale either has to integrate directly into existing media management systems—or replace them. Right now, there are a lot of tech companies at work retrofitting old technology or creating new technology that promises to make this a 2014 reality. It’s a horse race, and agencies are starting to place their bets. The winners are the one with the most extensible platforms that are good at integration, and they will be richly rewarded. The rest will fail, or become a point solution in someone else’s platform.

The Right Model: This is may be the most important factor in determining programmatic direct success. If you are charging anywhere north of 10% (and some would argue a LOT less than that) to help media buyers aggregate inventory, then you are not a “programmatic direct” technology company. You are an ad network, or media rep firm. The reason for industry consolidation is because disintermediation through technology has its own yield curve: The disruption that occurs always benefits the middle layer first, but markets always rationalize later. Mike Leo, former Operative CEO, told me about how another industry solved a similar problem that was occurring in the media business, where ad agencies were starting to rebel against specialized media buyers who in the middle of the transaction, with opaque pricing methodologies. The year was 1968, and agencies teamed up and decided that a standard rate of 15% was all they were willing to pay for television buying services (and then they eventually bought all of the media buying companies, but that’s another story). Anyway, markets always rationalize themselves, and right now even 15% feels like a big vigorish for agencies with ever-shrinking margins on their media practice.

Standards: It’s 2013, and we are still faxing IOs. This is largely because there are no accepted standards—and no protocol—for electronic orders.This is actually not a hard problem to solve, but getting adoption from buyers and sellers is what’s needed. Right now, a few companies are working with groups like the IAB to get real traction with standards, and we need that to succeed to make programmatic direct buying a scalable reality. Electronic orders suck a lot of the viscosity out of the deal pipeline, and start to let the machines do the grunt work of order processing, rather than a $50,000 junior media planner.

The good news is that there has been a tremendous amount of progress in 2013 on all of these initiatives. The promise of true programmatic direct buying is closer than ever, and there is enough real development behind the hype to make these dreams of efficient media buying a reality in the near future. In that future, it just may be possible for a buyer to use demand-side technology to aggregate the “fat middle” of premium mid tail publishers, and start to reward the middle class of inventory owners who are currently getting paid beer prices for champagne content.

Agencies are afraid of change, but change always happens. Is your manual workflow a “red stapler?”

But Solving the Right Problems are the Key to the Future

I once heard Terence Kawaja remark that “complexity is the agency’s best friend.” It’s hard to argue with that. Early digital agencies were necessary because doing things like running e-mail campaigns, building websites, and buying banner ads were really complicated. You needed nerdy guys who knew how to write HTML and understood what “Atlas” did. Companies like Operative grew admirable services businesses that took advantage of the fact that trafficking banner ads really sucked, and large publishers couldn’t be bothered to build those capabilities internally. The early days were great times for digital agencies. They were solving real problems.

Fast forward 13 years. Digital agencies are still thriving, mostly by unpacking other types of complexity. “Social media experts” were created to consult marketers on the new social marketing channel, “trading desks” launched to leverage the explosion of incomprehensible RTB systems, and terms like “paid, owned, and earned” were coined to complexify digital options. It’s hard being a marketer. So much easier to hand the digital keys over to an agency, and have them figure it all out.

Some of that complexity is dying, though.

Have you ever done any advertising on Google? It’s not that hard. You can get pretty good at search engine marketing quickly, and it doesn’t take anything more than common sense, an internet connection, and a credit card to start. Facebook advertising? Also dead easy. Facebook’s self-service platform is so intuitive that even the most hopeless Luddite can target to levels of granularity so minute that you can use it to reach a single individual. Today’s platforms leverage data and offer great user interfaces and user experience mechanisms to make the complex simple.

This has created the OpenTable effect. Remember when you had to call 8 different restaurants to get a Valentine’s Day reservation? What a pain in the ass. I used to always get to it late, and usually spend a few hours getting rejected before finding a table somewhere. Today, I log into OpenTable, type in “11743” and see all the available 8:30 reservations for two in Huntington. A few clicks, and I am locked in. Would I ever go back to doing it the old way? Sure, why not? Call my beeper if you need me. Please “911” me if it’s important.

So, with all of this innovation making the complex simple, and all of these platforms democratizing access to advertising inventory, analytics, and reporting, why are digital agencies still making a living off of the lowly banner ad? Is there a good business left in planning and buying digital display media?

Programmatic RTB is coming on strong, now representing the way almost a quarter of banner inventory is purchased. That’s a good thing. Platforms like Rubicon Project and Appnexus are making it easy to build great businesses on top of their complicated infrastructure. Marketers can hire an agency to trade for them, or maybe just build their own little team of smart people who can leverage technology. That seems to be happening more and more, making managing RTB either a specialist’s game, or not an option for the independent agency.

Really complicated, multi-channel, tentpole campaigns and sponsorships can never be automated. They represent about 5% of overall display spend, and that’s really where a digital agency’s firepower can be leveraged: the intersection of creativity and technology. That sector of digital involves a lot of what’s being called “native” today. Working with content owners and marketers to build great, branded experiences across the Web is where the smartest agencies should be right now.

How about the rest of the money spend on digital display—the 70% of money that goes through the transactional RFP space? A lot of agencies are still making their money buying reserved media, trafficking ad tags, and doing the dreaded billing and reconciliation. Marketers who pay on a cost-plus basis are starting to wonder whether spending money to have expensive agency personnel create and compare spreadsheets all day long is a good use of their money. Agencies that do not get paid for such work are seeing their margins shrink considerably, as they grind away money paying for low value tasks like ad operations. Clients don’t care how long it took you to get the click tag working on their 728×90. Just saying.

A lot of this viscosity within the guaranteed space is being solved by great “programmatic direct” technologies. Right now, you can use web-based systems to plan complex campaigns without using Excel or e-mail, and you can leverage web-based tools to buy premium inventory directly from great publishers—the kind of stuff not found inside RTB systems. Protocols and standards are being written that will, in a few short months, make the electronic IO a reality. Systems are being built with APIs that can enable trafficking to go away completely. Yes, you heard me. People should not have to ever touch JavaScript tags. That’s work for machines.

This future (“programmatic direct”) has been coming for a long time, but it is still met with resistance by agencies, some of whom are continue to benefit from complexity—and others who are (rightfully) scared of change and what it means for their business. Looking at legacy workflow systems, you wonder why they are so hesitant to leave them, but the cost of switching to new systems is high in terms of emotion and workplace disruption—and previous attempts to “simplify” agencies’ lives didn’t really work out that way.

So, how can digital agencies start to change, and embrace the new world of programmatic direct tools, so they can turn their energy to strategy and client care, rather than be an “expert” in processes that will eventually die?

Part of that is learning to recognize if you have a “wizard” on staff. The Wizard is the guy that has truly embraced complexity within the agency. He is the “systems guy” who knows how to pull complicated reports out of legacy workflow platforms. He probably knows who to write the occasional SQL query, and he knows where all the bodies (spreadsheets) are buried. When a web-based technology salesperson comes calling on the agency, and shows the CEO or VP of Media what web-based programmatic direct buying looks like, they are showing an agency a world where a lot of complexity is suddenly made simple. That demo shows the future of digital media buying: a directory-driven, centralized, web-based method of planning, buying, and serving inventory. Just like search! C-level agency executives and media people want it. They want their employees focused on strategy and analytics…not ad trafficking. But to get it, they invariably tell you to go see the Wizard. “Fred is our ‘systems guy.’ He’ll know whether this can work for us from a technical standpoint.”

That’s when innovation dies. Fred, the Wizard of the legacy systems, will shut down any innovation that comes his way. Complexity is Fred’s best friend. When you are the only guy that can pull a SQL query from your data warehouse, or reconcile numbers between SAP and your agency’s order management system, then you are a God. Fred is God…and he doesn’t want a downgrade. Complexity is the reason great digital agencies were built, and continue to thrive. Tomorrow’s big challenges are going to come from complexities in cross-channel delivery and attribution, and keeping up with new platforms that are delivering amazing native marketing opportunities, not being the next at reconciling ad delivery numbers from servers.

When you think of advertising technology in the display space, the first names you’re likely to think of are Google, PubMatic, Adobe, and AppNexus. But Microsoft? Not really top of mind, unless you are thinking of its disastrous aQuantive acquisition in 2007. Sure, every now and then MSFT will pick up the odd Rapt or Yammer, but is it really having a huge impact in the ad tech space? Even if you’re a regular AdExchanger reader, you’d be justified in thinking it’s not.

But you’d be 100% wrong.

Microsoft has been quietly running the inner ad-technology workings of digital display since the first banner ad was purchased in 1995. According to some recent research, the company’s ad-planning software boasts an amazing 76% market share among agency media planners. MediaVisor ranks a distant second with a measly 9.7 Almost nine in 10 planners who use Excel spend more than an hour a day using its software, while almost 35% use it for more than four hours per day[CO1] . [l2]

That software is called Microsoft Excel.

Released in 1985 (originally for Macintosh), Excel is nearly three decades old and has been powering digital-media planning since its inception. Combined with Outlook, Word, and PowerPoint in the Office suite of products, Microsoft tools have been central to the digital-media planning process for a long time. Planners plan in Excel, publishers pitch in Excel and PowerPoint, contracts are made in Word, and everything is communicated via Outlook. And then there are the billing and reconciliation tasks that occur inside spreadsheets. Nobody ever seems to wonder why more than $6 billion in digital display media transactions (representing nearly 70% of all ads sold) use Microsoft tools and the occasional fax machine.

While innovative companies have challenged the dominance of these systems in the past, early efforts fizzled. The complexities of modern digital-media planning, combined with the reluctance of agency planners to change their behavior, have hindered innovation. Looking at past and current “systems of record” for media buying, it’s no wonder planners are scared of change. If you have ever seen legacy agency operating systems, you wonder if a single dollar was ever spent on user experience or user interface design.

Why Programmatic-Direct Planners Use Excel

As an ad technology “evangelist” of sorts, it is my job to show agencies the future of digital-media planning. This is starting to be called programmatic buying, a term which encompasses both “programmatic direct” buying, which targets the transactional RFP business that accounts for the bulk – 70% – of digital display ads, and “programmatic RTB,” which accounts for the impression-by-impression purchases that represent another $2.4 billion, or 25[CO3] % of the pie.

Companies like MediaMath and AppNexus have made the latter category wildly efficient. Buyers don’t use Excel to create an audience-buying campaign across exchange inventory. Instead, they log into a web-based RTB platform.

For automating guaranteed display buys, though, Excel has become the default for media planners, even though if it doesn’t have the features of many web-based systems available. For example, Excel doesn’t track your changes. When planners change something, multiple files are created, and it’s easy for two people to work on a plan at the same time, duplicating work and botching it up. Excel isn’t Sarbanes-Oxley compliant, either. Agencies end up with thousands of Excel sheets on hard drives and servers, and a complicated file versioning and access system that makes replicating and tracking plans really difficult. Excel doesn’t integrate easily with other systems. At the file level, Excel is great. You can import and export Excel files into almost anything. But Excel can’t send out an RFP, or accept an order. Excel can’t automatically set an ad placement inside an ad server like DFA or MediaMind, or get Comscore updates. Excel is amazingly flexible, but it wasn’t built for media planning.

Today, the average digital-media plan costs nearly $40,000 to produce and takes as many as 42 steps to complete. That’s why, according to a recent Digiday survey, more than two thirds of agency employees will leave their jobs within the next two years. Digital-media planning should be fun and innovative, and young, smart people should want to be spending their time influencing how major brands leverage new technologies and media outlets to sell their products.

The reality is that young media planners are finding their days are filled with reconciling monthly invoices and ad delivery numbers. Have you noticed media planners’ eyes glazing over during your latest “lunch and learn?” That’s today’s young agency employees’ way of calling bullshit on ad tech. Our technology has been making their lives harder and their hours longer, rather than ushering in a new era of efficiency and performance.

How We Can Finally Beat Excel

I believe that dynamic is rapidly changing now. Buy-side technologies from innovative software companies, combined with offerings from sell-side players that are plugging into publisher ad servers are creating a programmatic future by building web-based, easy to use, and extensible platforms.Here are a few reasons these types of systems will start to get adoption:

Pushback on agency pricing models: Big agencies have been getting paid by the hour for years, but their clients are starting to push back on cost-plus pricing schemes. After exposure to self-service platforms and programmatic buying, they are getting used to seeing a larger percentage of their money applied to the media, and that trend is only likely to continue. Brand advertisers are demanding more efficiency in direct-to-publisher buys, and that means agencies must start to embrace programmatic direct technologies.

User interfaces and user experiences are improving: Young people plan media. They are used to really cool web-based technologies, such as Snapchat and Twitter. Today’s platforms not only centralize workflow and data, but increasingly come with something even more critical to gaining user adoption: a nice interface. When we start building tools that people want to use and a user experience that maps to the tasks being performed online, adoption will quickly increase.

Prevalence of APIs: Today’s platforms are being built in an open, extensible way that enables linkage with other systems. Since there are so many phases in modern digital media planning (research, planning, buying, ad serving, reporting, billing) it makes sense for platforms to be able to talk to one another. While some legacy APIs are not the best, they are getting better. Servers-to-server integrations make a lot more sense than 23-year-old planners updating spreadsheets. As David Kenny, CEO of The Weather Company, once remarked, “If you are using people to do the work of machines, you are already irrelevant .”

Because of these factors, I expect 2013 will be the year that programmatic direct buying changes from a fun concept for a planners’ “lunch and learn” to a reality. It’s time for us to finally get cracking on stealing some of Microsoft’s ad technology market share.

A long time ago, I was selling highly premium banner ad inventory to major advertisers. Part of a larger media organization, our site had great consumer electronics content tailored to successful professional and amateur product enthusiasts. The thing we loved most was sponsorships and advertorials. We practically had a micro-agency inside our shop, and we produced amazing custom websites, contests, and branded content sections for our best clients. They loved our creative approach, subject matter expertise, and association with our amazing brand. They still capture this revenue today.

The next thing we loved was our homepage and index page banner inventory. We sold all of our premium inventory—mostly 728×90 and 300×250 banners—by hand, and realized very nice CPMs. Back then, we were getting CPMs upwards of $50, since we had an audience of high-spending B2B readers. I imagine that today, the same site is running lots of premium video and rich media, and getting CPMs in the high teens for their above-the fold inventory and pre-roll in their video player. I was on the site recently, and saw most of the same major advertisers running strong throughout the popular parts of the site. Today, a lot of this “transactional RFP” activity is being handled by programmatic direct technologies that include companies like NextMark, Centro, iSocket, and AdSlot, not to mention MediaOcean.

What about remnant? We really didn’t think about it much. Actually, realizing how worthless most of that below-the-fold and deep-paged inventory was, we ran house ads, or bundled lots of “value added ROS” impression together for our good customers. Those were simple days, when monetization was focused on having salespeople sell more—and pushing your editorial team to produce more content worthy of high CPM banner placements.

Come to think of it, it seems like not much has changed over the last 10 years, with the notable exception of publishers’ approach to remnant inventory. About five years ago, they found some ad tech folks to take 100% of it off their hands. Even though they didn’t get a lot of money for it, they figured it was okay, since they could focus on their premium inventory and sales relationships. In doing some of those early network deals, I wondered who the hell would want millions of below-the-fold banners and 468x90s, anyway? Boy, was I stupid. Close your eyes for a year or two, and a whole “Kawaja map” pops up.

Anyhow, we all know what happened next. Networks used data and technology to make the crap they were buying more relevant to advertisers (“audience targeting”), and the demand side—seeing CPMs drop from $17 to $7, played right along. Advertisers LOVE programmatic RTB buying. It puts them in the driver’s seat, lets them determine pricing, and also (thanks to “agency trading desks”) lets them enhance their shrinking margins with a media vigorish. Unfortunately, for publishers, it meant that a rising sea of audience targeting capability only lifted the agency and ad tech boats. Publishers were seeing CPMs decline, networks eat into overall ad spending, DSPs further devaluing inventory, and self-service platforms like Facebook siphon off more of the pie.

How do publishers get control back of their remnant inventory—and start to take their rightful ownership of audience targeting?

That has now become simple (well, it’s simple after some painful tech implementation). Data Management Platforms are the key for publishers looking to segment, target, and expand their audiences via lookalike modeling. They can leverage their clients’ first party data and their own to drive powerful audience-targeted campaigns right within their own domains, and start capturing real CPMs for their inventory rather than handing networks and SSPs the lion’s share of the advertising dollar. That is step number one, and any publisher with a significant amount of under-monetized inventory would be foolish to do otherwise. Why did Lotame switch from network to DMP years ago? Because they saw this coming. Now they help publishers power their own inventory and get back control. Understanding your audience—and having powerful insights to help your advertisers understand it—is the key to success. Right now, there are about a dozen DMPs that are highly effective for audience activation.

What is even more interesting to me is what a publisher can do after they start to understand audiences better. The really cool thing about DMPs is that they can enable a publisher to have their own type of “trading desk.” Before we go wild and start taking about “PTDs” or PTSDs or whatever, let me explain.

If I am BigSportsSite, for example, and I am the world’s foremost expert in sports content, ranking #1 or #2 in Comscore for my category, and consistently selling my inventory at a premium, what happens when I only have $800,000 in “basketball enthusiasts” in a month and my advertiser needs $1,000,000 worth? What happens today is that the agency buys up every last scrap of premium inventory he can find on my site and others, and then plunks the rest of her budget down on an agency trading desk, who uses MediaMath to find “basketball intenders” and other likely males across a wide range of exchange inventory.

But doesn’t BigSportsSite know more about this particular audience than anyone else? Aren’t they the ones with historical campaign data, access to tons of first-party site data, and access to their clients’ first party data as well? Aren’t they the ones with the content expertise which enables them to see what types of pages and context perform well for various types of creative? Also, doesn’t BigSportsSite license content to a larger network of pre-qualified, premium sites that also have access to a similar audience? If the answer to all of the above is yes, why doesn’t BigSportsSite run a trading desk, and do reach extension on their advertisers’ behalf?

I think the answer is that they haven’t had access to the right set of tools so far—and, more so, the notion of “audience discovery” has somehow been put in the hands of the demand side. I think that’s a huge mistake. If I’m a publisher who frequently runs out of category-specific inventory like “sports lovers,” I am immediately going to install a DMP and hire a very smart guy to help me when I can’t monetize the last $200,000 of an RFP. Advertisers trust BigSportsSite to be the authority in their audience, and (as importantly) the arbiter of what constitutes high quality category content.

Why let the demand side have all of the fun? Publishers who understand their audience can find them on their own site, their clients’ sites, across an affiliated network of partner sites, and in the long tail through exchanges. These multi-tiered audience packages can be delivered through one trusted partner, and aligned with their concurrent sponsorship and transactional premium direct advertising.

Maybe we shouldn’t call them Publisher Trading Desks, but every good publisher should have one.

I was recently at a conference, and took a picture of a PowerPoint slide that I thought was pretty interesting. It showed the growth of tweets about television from Q2 2011 to last quarter. Basically, nobody was tweeting anything a few years ago, and then there were over 18 million unique people tweeting about TV in Q4 2012, representing a 182% year-over-year growth rate. If you are a modern marketer that spends money on television advertising, there are some implications in this data worth looking at.

Are you in the conversation?

Back in the 1980s, I would sometimes go to Times Square to see horror movies. The theatres were uniformly crumby, but the people were the best. Times Square movie theatres always featured an audience willing to give Jamie Curtis’ Halloween character plenty of advice in each scene. In fact, between the chatter and screaming, you could hardly hear the film. That was what passed for “social viewing” in the old days. Today, we are discovering that people still like to share viewing experiences together, and Twitter and other social tools lets you make every television show an Oscar party you can attend in your pajamas. Brand advertisers backing a particular show want the glow of good comedy or drama, and now extending that association may mean inserting yourself into the conversation via a Sponsored Tweet. What’s really interesting about that is your message can be received during the action, without interrupting.

Less TV, More Tweet

The rise of “Social TV” gives brand marketers yet another dimension to ponder as well. With a show’s active and engaged community just a Tweet away, how much media should you allocate to thirty second spots, and how much should go towards the social element? Moreover, social TV means that every consumer seeing your ad can get the chance to interact and talk back socially. We are seeing marketers hashtag their ads and drop into the social stream of conversation. Although this is still a form of “interruption marketing,” it’s the closest that brands have gotten to being a part of, rather than disturbing, the entertainment in a long time. These digital “native advertising” opportunities are proving effective, and starting to take market share away from commoditized 300×250 display advertising units.

Can your company dunk in the dark?

The latest test for marketers is The Oreo Challenge or, more simply put, do I have a social strategy for taking advantage of news and events? Although it seemed like a no-brainer during the Superbowl, “you can still dunk in the dark” was the result of a contemplated strategy. Oreo’s very responsive tweet is a phenomenon that digital marketers are still talking about—the kind of lightning on a bottle that produces tens of millions of dollars in “earned” media. But getting there requires your marketing team and agency to truly understand everything about the brand they are promoting. If your team can’t automatically speak in the brand’s “voice” and doesn’t truly understand the brand attributes and values, you can’t automatically respond to opportunity in the social space. Teams that live and breathe their brand—and, more importantly, their brand’s key constituency—must be trusted to speak socially…and sometimes loudly, if the occasion warrants it. Of course, there is a good chance your joke will go flat, but that’s okay when you are among your television “friends.”

Should publishers go beyond the boundaries of their own inventory to sell “reach extension” packages to their clients? Publishers have long struggled with the problem of how to deliver a $100,000 campaign when they only have $90,000 of inventory. Without a strong partner network, the natural answer to that question used to be click arbitrage, an expensive and risky method of campaign fulfillment that often came with less than desirable site visitors.

These days there are several major factors that make reach extension a great opportunity for publishers, rather than a sales mechanism that strays outside their sore realm of expertise.

Publishers with premium inventory sell in three principle ways: Their best inventory is sold in large, customized “tent pole” sales; their standardized premium IAB units are sold through the transactional RFP process; and the rest is sold programmatically, through their remnant daisy chain. They do the first thing really well, especially for big branded advertisers, where they act like a mini creative/media agency to build custom programs. Publishers are also getting much better at the transactional business by leveraging great tools to bring efficiency to RFP response and enabling better demand-side access to their premium inventory (AdSlot, iSocket). The third thing (“remnant”) is the ball publishers continue to fumble, even though enabling an “owned” programmatic channel is getting easier for publishers every day.

Data management is the obvious solution. With the right tools, publishers no longer have to rely on third parties to understand the composition of their audience. The combination of a publisher’s CRM data and site tag data, ingested into one of a dozen amazing DMPs can enable them to segment and target their audience on the fly. Want “auto enthusiasts” on my site? Not only can I sell you a highly creative, customized program and back it up with a large share-of-voice in standard IAB banners within the site section—but now I can find your own customers right on my site…and on Facebook as well.

The last part of that equation (leveraging the client’s first-party CRM data) is where today’s reach extension differs from sending your excess buy to ContextWeb or AudienceScience, as you would in the old days. Now, publishers can find advertisers’ customers within their own site or publisher network and retarget them. Better yet, pubs can help advertisers put that same first-party data to work on exchanges, including FBX, where match rates (and performance) are high. Really advanced publishers will leverage their DMP to model the audience advertisers are trying to reach, and build a custom lookalike model which can find “alike” audiences within the publisher network itself, or across the exchanges.

Publishers are acting more and more like agencies when it comes to the big premium sales that take multidisciplinary talent to pull off (sales, media, creative, development). Why shouldn’t they act like an agency (or, more specifically, an agency trading desk) when it comes to helping their clients with reach extension goals? If I am a publisher, and my client comes to me looking for the audience I specialize in, I should be able to tell the advertiser how to reach that audience—starting on my own site, but also across the Web in general. The right data management strategy and tools enable publishers to cover all three legs of the buy: sponsorship, transactional, and programmatic.

[This appeared as part of AdMonsters invaluable Audience Extension Playbook, available here.]

Understanding Social Affinity Data

Marketers are increasingly turning to social platform data to understand their customers, and tapping into their social graphs to reach more of them. Facebook “likes” and Twitter “follows” are religiously captured and analyzed, and audience models are created—all in the service of trying to scale the most powerful type of marketing of all: Word-of-mouth. With CRM players (like Salesforce, who recently acquired Buddy Media and Radian6) jumping into the game, digitally-derived social data is now an established part of traditional marketing.

But, are marketers actually finding real signals amid the noise of social data? In other words, if I “like” Lady Gaga, and you “like” Lady Gaga, and my ten year old daughter also “likes” Lady Gaga, then what is the value of knowing that? If I want to leverage social data to enrich my audience profiles, and try and get the fabled “360 degree” view of my customer, “likes” and “follows” may contribute more noise than insight. I recently sat down with Colligent’s Sree Nagarajan to discuss how brand marketers can go beyond the like, and get more value out of the sea of social data.

Colligent (“collectively intelligent,” if you like) goes beyond “likes” and actually measures what people do on social sites. In other words, if you merely “like” Lady Gaga, you are not measured, but if you post a Lady Gaga music video, you are. By scraping several hundred million Facebook profiles, and accessing the Twitter firehose of data, Nagarajan’s company looks at what people are socially passionate about—and matches it against other interests. For example, the data may reveal that 5% of Ford’s socially active fanbase is also wild about NASCAR. That’s great to know. The twist is that Colligent focuses on the folks who are nuts about NASCAR—and like Ford back. That’s called mutual engagement and, arguably, a more powerful signal.

Nagarajan’s focus on this type of data has many questioning the inherent value of targeting based on social media membership. “In any social network’s lifecycle, likes (or ‘follows’ or friends) start out as genuine signals of brand affinity. However as more and more like the page their audience gets increasingly diluted, making likes less of an indicator of brand’s true audience. True engagement as measured by comments, photo posts, re-tweets, hashes, etc. became much better indicators of brand affinity and engagement.”

Colligent data recently convinced Pepsi to choose Nicki Minaj as their spokesperson, since the data revealed a strong correlation between socially activated Pepsi and Minaj fans. Think about that for a second. For years, major brands have used softer, panel-based data (think “Q Score”) to decide what celebrities are most recognizable, and capture the right brand attributes. Now, getting hard metrics around the type of people who adore your brand are just a query away. Digital marketers have been talking about “engagement” for years, and have developed a lexicon around measurement including “time spent” and “bounce rate.” Social affinity data goes deeper, measuring true engagement. For Nagarajan, “In order for the engagement to be truly effective, it needs to be measured from both sides (mutual engagement). The parallel is a real-world relationship. It’s not enough for me to like you, but you have to like me for us to have a relationship. Mapped to the brand affinity world, it’s not enough for Pepsi fans to engage with Nicki Minaj; enough Nicki fans have to engage with Pepsi (more than the population average on both sides) to make this relationship truly meaningful and thus actionable. When true engagement is married with such mutual engagement, the result is intelligence that filters the noise in social networks to surface meaningful relationships.”

So, what else can you learn from social affinity data? With so many actively engaged fans and followers, throwing off petabytes of daily data, these networks offer a virtual looking glass for measuring real world affinities. If you think about the typical Facebook profile, you can see that many of the page memberships are driven by factors that exist outside the social network itself. That makes the data applicable beyond digital:

Television: Media planners can buy the shows, networks, and radio stations that a brand’s fans are highly engaged with.

Public Relations: Flacks can direct coverage towards the media outlets a brand’s fans are engaged with.

Sponsorships: Marketers can leverage affinity data to determine which celebrity should be a brand’s spokesperson.

Search: SEM directors can expand keyword lists for Google and Facebook buys using social affinity-suggested keywords.

Display: Discover what sites Ford’s socially activated consumers like, and buy those sites at the domain level to get performance lift on premium guaranteed inventory buys.

Are we entering into a world in which marketers are going to use this type of data to fundamentally change the way they approach media buying? What does it mean to “buy brand?” Sree Nagarajan sees this type of data potentially transforming the way offline and online media planners begin their process. “Much of the audience selection options available in the market today are media based. Nielsen defines TV audience, Arbitron radio, ComScore digital sites, MRI magazines, etc. Brand marketers are forced to define their audiences in the way media measures audience: by demographics (e.g., 18-49 male),” remarks Sree. “Now, for the first time, social data allows marketers to define audiences based on their ownbrand and category terms. Now, they can say ‘I want to buy TV shows watched by Pepsi and more generally, Carbonated Soft Drinks audience.’ This will truly make marketing brand-centric instead of media-centric. Imagine a world where brand and category GRPs can be purchased across media, rather than GRPs in a specific media.”

Look for this trend to continue, especially as company’s become more aggressive aligning their CRM databases with social data.

Getting back control over their inventory is giving publishers a lot to think about.

“We want to make sure that we’re controlling what happens with data . . . we want to make sure we control pricing. Control’s a very important message. We don’t want there to be a cottage industry built on our backs” – Nick Johnson, SVP, NBC Universal

What do publishers really want? It’s simple, really: Power and control. In order to survive the ad technology era, publishers need the power to monetize their audiences without relying on third parties, and complete control over how they sell their inventory. In this era of “Big Data,” there is a fire hose stream of tremendously valuable information for publishers to take advantage of, such as keyword-based search data, attitudinal survey data, customer declared data from forms, page-level semantic data, and all the 3rd party audience data you can shake a stick at.

All of this data (cheap to produce, and ever-cheaper to store) has given rise to companies who can help publishers bring that data together, make sense of it, and use it to their advantage. Currently, ad technology companies have been using the era of data to their advantage, utilizing it to create vertical ad networks, ad exchanges, data exchanges, DSPs, and a variety of other smart-sounding acronyms that ultimately purport to help publishers monetize their audiences, but end up monetizing themselves.

Rather than power the ad tech ecosystem, what if data could actually help publishers take back their audiences? If “data is the new gold” as the pundits are saying, then smart publishers should mine it to increase margins, and take control of their audiences back from networks and exchanges. Here are the five things a good data management platform should enable them to do:

Unlock the Value of 1st Party Data: Publishers collect a ton of great data, but a lot of them (and a LOT of big publishers) don’t leverage it like they should. Consider this recent stat: according to a recent MediaPost article, news sites only use in-site audience targeting on 47% of their impressions, as opposed to almost 70% for Yahoo News. By leveraging site-side behavioral data, combined with CRM data and other sources, it is possible to layer targeting on almost every impression a publisher has. Why serve a “blind” run-of-site (ROS) ad, when you can charge a premium CPM for audience-targeted inventory?

Decrease Reliance on 3rd Parties: The real reason to leverage a DMP is to get your organization off the 3rd party crack pipe. Yes, the networks and SSPs are a great “plug and play” solution (and can help monetize some “undiscoverable” impressions), but why are publishers selling raw inventory at $0.35 and letting the people with the data resell those impressions for $3.50? It’s time to turn away those monthly checks, and start writing some to data management companies that can help you layer your own data on top of your impressions, and charge (and keep) the $3.50 yourself. Today’s solutions don’t have to rely on pre-packaged 3rd party segments to work, either, meaning you can really reduce your data costs. With the right data infrastructure, and today’s smart algorithm-derived models, a small amount of seed data can be utilized to create discrete, marketable audience segments that publishers can own, rather than license.

Generate Unique Audience Insights: Every publisher reports on clicks and impressions, but what advertisers are hungry for (especially brand advertisers) are audience details. What segments are most likely to engage with certain ad content? Which segments convert after seeing the least amount of impressions? More importantly, how do people feel about an ad campaign, and who are they exactly? Data management technology is able to meld audience and campaign performance data to provide unique insights in near real-time, without having to write complicated database queries and wait long times for results. Additionally, with the cost of storing data getting lower all the time, “lookback windows” are increasing, enabling publishers to give credit for conversion path activity going back several months. Before publishers embraced data management, all the insights were in the hands of the agency, who leveraged the data to their own advantage. Now, publishers can start to leverage truly powerful data points to create differentiated insights for clients directly, and provide consultative services with them, or offer them as a value-added benefit.

Create New Sales Channels: Before publisher-side data management, when a publisher ran out of the Travel section impressions, he had to turn away the next airline or hotel advertiser, or offer them cheap ROS inventory. Now, data management technology can enable sales and ops personnel to mine their audience in real time and find “travel intenders” across their property—and extend that type of audience through lookalike modeling, ensuring additional audience reach. By enabling publishers to build custom audience segments for marketers on the fly, a DMP solution ensures that no RFP will go unanswered, and ROS inventory gets monetized at premium prices.

Create Efficiency: How many account managers does it take to generate your weekly ad activity reports? How much highly paid account management time are publishers burning by manually putting together performance reports? Why not provide an application that advertisers can log into, set report parameters, and export reports into a friendly format? Or, better yet, a system that pre-populates frequent reports into a user interface, and pushes them out to clients via an e-mail link? You would think this technology was ubiquitous today, but you would be wrong. Ninety-nine percent of publishers still do this the hard (expensive) way, and they don’t have to anymore.

It’s time for publishers to dig into their data, and start mining it like the valuable commodity it is. Data used to be the handcuffs which kept publishers chained to the ad technology ecosystem, where they grew and hosted a cottage industry of ad tech remoras. The future that is being written now is one of publishers’ leveraging ad technologies to take back control, so they can understand and manage their own data and have the freedom to sell their inventory for what it is truly worth.

Data management may seem like a high hurdle to jump for some agencies.

Twenty years after the first banner ad, the programmatic media era has firmly taken hold.

The holy grail for marketers is a map to the “consumer journey,” a circuitous route filled with multiple addressable customer touchpoints. With consumers spending more of their time on mobile devices – and interacting with brands like never before through social channels, review sites, pricing comparison sites and apps – how can marketers influence customers everywhere they encounter a brand?

It’s a tough nut to crack, but starting to become an achievable reality to companies dedicated to collecting, understanding and activating their data. Marketers are starting to turn toward data-management platforms (DMP), which help them connect people with their various devices, develop granular audience segments, gain valuable insights and integrate with various platforms where they can activate that data. In addition to technology, marketers also have to configure their entire enterprises to align with the new data-driven realities on the ground.

The question is: Where do marketers turn for help with this challenging, enterprise-level transition?

Many argue that agencies cannot support the type of deep domain expertise needed for the complicated integrations, data science and modeling that has become an everyday issue in modern marketing. But should data-management software selection and integration be the sole province of the Accentures and IBMs of the world, or is there room for agencies to play?

For lots of software companies, having an agency in between an advertiser and their marketing platform sounds like a problem to overcome, rather than a solution. Many ad tech sellers out there have lamented the process of the dreaded agency “lunch and learn” to develop a software capability “point of view” for a big client.

Yet there are highly compelling ways agencies add value to the software selection process. The best agencies insert themselves into the data conversation and use their media and creative expertise to influence what DMPs marketers choose, as well as their role within the managed stack.

From Digital To Enterprise

It makes perfect sense that agencies are involved with data management. The first intersection of data and media added the “targeting” column to the digital RFP. Agencies have started to evolve beyond the Excel-based media planning process to start their plans with an audience persona that is developed in conjunction with their clients. Today, plans begin with audience data applied to as many channels as are reachable. Audience data has moved beyond digital to become universal.

Agencies have also been at the tip of the spear, both from an audience research standpoint (understanding where the most relevant audiences can be found across channels) and an activation standpoint (applying huge media budgets to supply partners). Since they are on the front lines of where media dollars are expressed, they often get the first practical look at where data impacts consumer engagement. During and after campaigns conclude, the agency also owns the analytics piece. How did this channel, partner and creative perform? Why?

Having formerly limited agencies to campaign development and execution, marketers are now turning to the collected expertise of their agency media and analytics teams and asking them to embed the culture of audience data into their larger organization. When it’s time to select the DMP, the internal machine that drives the people-based marketing enterprise, the agency is naturally called upon.

Data Management Is About Ownership

Although a small portion of innovative marketers have begun leveraging DMP technology and taken media execution “in-house,” the vast majority stills relies on agencies and ad tech platform partners to operate their stacks through a managed services approach. Whether a marketer should own the capability to manage its own ad technology stack is a matter of choice, but data ownership shouldn’t be. Brands may not want to own the process of applying audience data to cross-channel media, but they absolutely must own their data.

Where Agencies Play in Data Management

The Initial Approach: Most agencies have experience leveraging marketers’ first-party data through retargeting on display advertising. In an initial DMP engagement, marketers will rely on their agencies to build effective audience personas, map those to available attributes that exist within the marketer’s taxonomy and apply the segments to existing addressable channels. Marketers can and should rely on past campaign insights, attribution reports and other data insights from their agencies when test-driving DMPs.

Connect the Dots: For most marketers, agencies have been the de facto connector between their diverse platforms. Media teams operate display, video and mobile DSPs, ad-serving platforms and attribution systems. Helping a marketer and their DMP partner tie these execution platforms together and understand audience data and the performance data generated is a critical part of a successful DMP implementation.

Operator: Last, but not least, is the agency as operator of the DMP. Marketers want their data safely protected in their own DMP, with strong governance rules around how first-party data is shared. They also need a hub for using third-party data and integrating it with various execution and analytics platforms. Marketers may not want to operate the DMP themselves, though. Agencies can win by helping marketers wring the most value from their platforms.

Marketers have strong expertise in their products, markets and customer base – and should focus on their core strengths to grow. Agencies are great at finding audiences, building compelling creative and applying marketing investment dollars across channels, but are not necessarily the right stewards of others’ data.

Future success for agencies will come from helping marketers implement their data-management strategy, align their data with their existing technology stack and return insights that drive ongoing results.

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about.me

@chrisohara

As a leading expert on programmatic approaches to digital media, I write frequently on the industry for publications including AdExchanger and Econsultancy. I am also the author of 6 best-selling books including Great American Beer, and Hot Toddies, the classic holiday cocktail book, from Random House.